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dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/console.log b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/console.log deleted file mode 100644 index 42b82886c1200e82153ffc052546a232f0fbc2e4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 17:11:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:11:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:11:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:11:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:11:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:11:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:11:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:11:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/config.yaml -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_bg0.1_rm0.5'] -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_bg0.1_rm0.5 -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.json -[06-21 17:11:42|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:22:14|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 -[06-21 17:22:14|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:22:16|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/debug.log b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/debug.log deleted file mode 100644 index 71aa625dfd5af399a584268d501c9de201443924..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 17:11:16|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 17:11:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:11:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:11:28|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:11:28|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:11:29|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 17:11:29|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 17:11:29|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 17:11:29|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 17:11:29|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 17:11:29|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 17:11:29|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 17:11:29|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 17:11:29|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 17:11:29|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 17:11:29|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 17:11:29|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 17:11:29|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 17:11:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 17:11:30|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 17:11:30|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 17:11:30|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:11:30|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 17:11:30|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:11:30|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 17:11:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:11:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:11:31|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 17:11:31|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 0.98 s -[06-21 17:11:34|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 17:11:34|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.07 s -[06-21 17:11:35|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.89 s -[06-21 17:11:35|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.42 s -[06-21 17:11:35|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.42 s -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 17:11:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 17:11:35|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 17:11:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:11:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:11:36|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 17:11:36|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 17:11:36|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 17:11:36|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 17:11:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:11:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:11:40|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 17:11:40|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 17:11:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:11:40|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.08 s -[06-21 17:11:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:11:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:11:40|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:11:41|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:41|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:11:42|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:11:42|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 17:11:42|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/config.yaml -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_bg0.1_rm0.5'] -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_bg0.1_rm0.5 -[06-21 17:11:42|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_Building_2b_step35_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.json -[06-21 17:11:42|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:11:42|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4 -[06-21 17:11:42|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 176 -[06-21 17:11:43|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 17:11:43|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 17:11:43|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:11:43|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:11:43|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:11:43|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:11:43|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:12:01|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:17:08|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 17:17:08|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 17:17:08|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:17:08|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:17:08|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:17:08|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:17:08|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:17:11|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:22:13|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 314.19064437551424 -[06-21 17:22:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:22:14|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 -[06-21 17:22:14|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:22:14|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:22:16|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.json b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.json deleted file mode 100644 index 4d25de7856fa26b992f83ed06ef8e2999204ad20..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_Building_2b_step35_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.mp4 deleted file mode 100644 index 4fd8faee28d646374837b95ec27bd2da8bc283b8..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:1fa9a15519bb9b59b557e08ac5d9bfee9c8e7d5d475e54e3ce45652beea7cea4 -size 2663720 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.txt b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.txt deleted file mode 100644 index 213c470aee0671b5a985429e153c07e4efd43cd3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 0efd7167248d6dc726173bc526b89fbe81ff601c..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/rainy_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:7485b050e777b96bed1aa6964ab1403dcc5f780868ddb049bf7c86e10fb761ef -size 1676430 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/spec.json b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/spec.json deleted file mode 100644 index ee488003ca31043e6ad02f8555512ddf8f923cfa..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_Building_2b_step35_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/config.yaml b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/config.yaml deleted file mode 100644 index eb27f82317c657a274c3c0109befec64f25f96ac..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/console.log b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/console.log deleted file mode 100644 index 49addc25397b5c701d986a85e506717accd8afea..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 17:22:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:22:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:22:38|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:22:38|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:22:39|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:22:39|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:22:43|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:22:43|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/config.yaml -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_bg0.1_rm1'] -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_bg0.1_rm1 -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.json -[06-21 17:22:45|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:33:28|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1_control_edge.mp4 -[06-21 17:33:28|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:33:30|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/debug.log b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/debug.log deleted file mode 100644 index eba3ab953e195026199f416eb9fa3057daa37458..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 17:22:19|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 17:22:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:22:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:22:31|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:22:32|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:22:32|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 17:22:32|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 17:22:32|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 17:22:32|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 17:22:32|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 17:22:32|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 17:22:32|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 17:22:32|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 17:22:32|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 17:22:32|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 17:22:32|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 17:22:32|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 17:22:32|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 17:22:32|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 17:22:33|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:22:33|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 17:22:33|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:22:33|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 17:22:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:22:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:22:34|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 17:22:34|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.30 s -[06-21 17:22:37|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 17:22:37|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 17:22:38|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 17:22:38|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.11 s -[06-21 17:22:38|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.11 s -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 17:22:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 17:22:38|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 17:22:38|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:22:38|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:22:39|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 17:22:39|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 17:22:39|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 17:22:39|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 17:22:39|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:22:39|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:22:43|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 17:22:43|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 17:22:43|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:22:43|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.12 s -[06-21 17:22:43|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:22:43|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:22:43|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:22:44|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.5.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.5.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.5.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.5.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.5.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.5.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.5.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:44|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:22:45|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:22:45|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 17:22:45|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/config.yaml -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_bg0.1_rm1'] -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_bg0.1_rm1 -[06-21 17:22:45|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_Building_2b_step35_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.json -[06-21 17:22:45|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:22:45|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4 -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 17:22:45|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 17:22:46|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:22:46|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:22:46|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:22:46|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:22:46|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:23:04|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:28:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 17:28:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 17:28:19|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:28:19|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:28:19|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:28:19|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:28:19|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:28:22|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:33:25|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 318.4213521160418 -[06-21 17:33:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:33:28|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1_control_edge.mp4 -[06-21 17:33:28|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:33:28|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:33:30|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.json b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.json deleted file mode 100644 index b6fdbbfc4f15c099639f7f81a643e0754a39d393..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_Building_2b_step35_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.mp4 deleted file mode 100644 index cec882893b7b320019cdc420e519db78a98759eb..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:f5e1f96bf886d0b52310629e6aef9fa261d5e56a1acc4a1f1be4977bbb6fb8ee -size 6913917 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.txt b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.txt deleted file mode 100644 index 213c470aee0671b5a985429e153c07e4efd43cd3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 3d26387ac3b10e58e0ccf5d217c25453be731eef..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/rainy_Building_2b_step35_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:dc0a0df691bf27491874ae8aa19c94186b1824969467acc8e5ec0befdad2d3db -size 2163198 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/spec.json b/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/spec.json deleted file mode 100644 index 9edcf4abb325ee6464d3845d839151f3dad18412..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.1_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_Building_2b_step35_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/config.yaml b/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/config.yaml deleted file mode 100644 index 2e1b48a44d968e4c211f1089997a7ebd0156e923..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/console.log b/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/console.log deleted file mode 100644 index 4b14e1ade96b88933823705799709f63517d2548..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 17:35:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:35:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:35:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:35:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:35:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:35:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:35:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:35:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/config.yaml -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_bg0.5_rm1'] -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_bg0.5_rm1 -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.json -[06-21 17:35:36|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:46:10|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1_control_edge.mp4 -[06-21 17:46:10|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:46:12|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/debug.log b/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/debug.log deleted file mode 100644 index 485bc75c3a05f6dc22441f10a2de6649ca75e7db..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 17:34:24|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 17:34:40|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:34:40|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:35:19|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:35:19|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:35:19|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 17:35:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 17:35:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 17:35:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 17:35:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 17:35:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 17:35:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 17:35:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 17:35:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 17:35:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 17:35:20|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 17:35:20|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 17:35:20|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 17:35:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 17:35:20|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:35:20|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 17:35:20|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:35:20|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 17:35:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:35:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:35:21|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 17:35:21|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.04 s -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 17:35:25|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.83 s -[06-21 17:35:25|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.12 s -[06-21 17:35:25|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.12 s -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 17:35:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 17:35:25|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 17:35:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:35:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:35:27|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 17:35:27|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 17:35:27|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 17:35:27|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 17:35:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:35:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:35:33|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 17:35:33|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 17:35:33|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:35:33|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 12.84 s -[06-21 17:35:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:35:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:35:34|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:35:36|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:35:36|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:35:36|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 17:35:36|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 17:35:36|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/config.yaml -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_bg0.5_rm1'] -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_bg0.5_rm1 -[06-21 17:35:36|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_Building_2b_step35_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.json -[06-21 17:35:36|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:35:36|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:35:36|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 17:35:36|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4 -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 17:35:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 17:35:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:35:38|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:35:38|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:35:38|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:35:38|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:35:56|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:41:03|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 17:41:03|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 17:41:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:41:03|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:41:03|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:41:03|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:41:03|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:41:05|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:46:09|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 314.6682530285325 -[06-21 17:46:09|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:46:10|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1_control_edge.mp4 -[06-21 17:46:10|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:46:10|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:46:12|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.json b/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.json deleted file mode 100644 index 58980c249b871b345948deadeb6a88d332b14e8a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_Building_2b_step35_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.mp4 deleted file mode 100644 index 5b72be4ed0685801b08bf39d9be7758d21ab0005..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:795ae3d681fecd66f6b3eef3e51102b16760e48da1e1f7cab7cc10504f2d4ef3 -size 6987287 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.txt b/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.txt deleted file mode 100644 index 213c470aee0671b5a985429e153c07e4efd43cd3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index 5fc5f4b057f706d7a54074ed1ded7dfa297ca3fb..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/rainy_Building_2b_step35_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:c49968d42faa0f81106ab6e92fceb2d588c040f9c4603f3d5822f112aa2bddeb -size 2200693 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/spec.json b/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/spec.json deleted file mode 100644 index 21ef46838eed6c84e9ac45a7094293a3e2461056..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_bg0.5_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_Building_2b_step35_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml deleted file mode 100644 index de26615a19dfdb0e236186fd4db8082aa06f727e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/console.log b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/console.log deleted file mode 100644 index a957506110fdc5e5d263c3ca2e0b4f42c7786010..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 17:46:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:46:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:46:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:46:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_masked_bg0.1_rm0.5'] -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_masked_bg0.1_rm0.5 -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.json -[06-21 17:46:58|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 17:57:30|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 -[06-21 17:57:30|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:57:32|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/debug.log b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/debug.log deleted file mode 100644 index 8a5f40f69145990922bc5aeefc7100087217cae0..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 17:46:24|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 17:46:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:46:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:46:44|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:46:45|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:46:45|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 17:46:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 17:46:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 17:46:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 17:46:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 17:46:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 17:46:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 17:46:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 17:46:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 17:46:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 17:46:46|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 17:46:46|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 17:46:46|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 17:46:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 17:46:46|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:46:46|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 17:46:46|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:46:46|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 17:46:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:46:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:46:47|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 17:46:47|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.09 s -[06-21 17:46:51|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:46:51|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.10 s -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.10 s -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 17:46:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 17:46:52|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:46:52|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 17:46:52|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 17:46:52|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:46:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:46:56|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 17:46:56|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 17:46:56|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:46:56|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 9.96 s -[06-21 17:46:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:46:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:46:57|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:46:58|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:46:58|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:46:58|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 17:46:58|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 17:46:58|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_masked_bg0.1_rm0.5'] -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_masked_bg0.1_rm0.5 -[06-21 17:46:58|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_Building_2b_step35_masked_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.json -[06-21 17:46:58|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:46:58|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 17:46:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 17:46:58|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 17:46:58|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:46:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4 -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 176 -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4 -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:46:59|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:46:59|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:46:59|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:47:17|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:52:24|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 17:52:24|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 17:52:24|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:52:24|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:52:24|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:52:24|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:52:24|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:52:27|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:57:29|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.9915293720551 -[06-21 17:57:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:57:30|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 -[06-21 17:57:30|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:57:30|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:57:32|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.json b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.json deleted file mode 100644 index 60854cb4b0e4af474ea1d2a240b6701de6fe19b7..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_Building_2b_step35_masked_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.mp4 deleted file mode 100644 index 753858ec3baeae943cfa34839f58a0acf7078636..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:871deb22c33fdacc4f26aebbaa07321f81260f538cd6d24020309f596baec7dc -size 1772032 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.txt b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.txt deleted file mode 100644 index 213c470aee0671b5a985429e153c07e4efd43cd3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 1e3fdf83df724d46887a4db0ccbf64523b831f11..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/rainy_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:2daa4d0d626f944990f4d0367286b85b6a90438904edb6d808ccca374f9be20f -size 1076029 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/spec.json b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/spec.json deleted file mode 100644 index 22672907af1522ab3ca8f9511bb81b4c2259ee29..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "rainy_Building_2b_step35_masked_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/config.yaml b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/config.yaml deleted file mode 100644 index 7831e174b0ec8ffa8b2ff70a4b8fbc6c504031b3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/console.log b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/console.log deleted file mode 100644 index 300b3009568fba4cead0aa5bad3eb4f894e8d60d..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 17:59:09|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:59:09|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:59:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:59:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:59:34|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:59:34|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:59:38|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:59:38|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/config.yaml -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_masked_bg0.1_rm1'] -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_masked_bg0.1_rm1 -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.json -[06-21 17:59:40|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 18:10:22|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 -[06-21 18:10:22|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 18:10:23|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/debug.log b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/debug.log deleted file mode 100644 index b4a9f66bdbc5a2210ff30eba4be882ee509535b7..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 17:57:35|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 17:57:36|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:57:36|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:58:49|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:58:57|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:59:03|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 17:59:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 17:59:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 17:59:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 17:59:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 17:59:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 17:59:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 17:59:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 17:59:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 17:59:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 17:59:06|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 17:59:07|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 17:59:08|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 17:59:08|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 17:59:08|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 17:59:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 17:59:08|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:59:08|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 17:59:08|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 17:59:08|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 17:59:09|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:59:09|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:59:16|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 17:59:17|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 8.25 s -[06-21 17:59:20|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:59:20|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:20|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:59:21|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 5.19 s -[06-21 17:59:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 5.96 s -[06-21 17:59:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 9.23 s -[06-21 17:59:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 9.23 s -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 17:59:26|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 17:59:26|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 17:59:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:59:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:59:27|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 17:59:27|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 17:59:27|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 17:59:34|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 17:59:34|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:59:34|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:59:38|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 17:59:38|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 17:59:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:59:38|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 30.08 s -[06-21 17:59:38|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 17:59:38|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:59:39|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 17:59:40|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:59:40|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:59:40|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 17:59:40|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 17:59:40|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/config.yaml -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_masked_bg0.1_rm1'] -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_masked_bg0.1_rm1 -[06-21 17:59:40|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_Building_2b_step35_masked_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.json -[06-21 17:59:40|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:59:40|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 17:59:40|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 17:59:40|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 17:59:43|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:59:44|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 17:59:51|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 17:59:51|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 17:59:51|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 17:59:51|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 17:59:51|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4 -[06-21 17:59:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:59:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4 -[06-21 17:59:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:59:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 17:59:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 17:59:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:59:52|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:59:52|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:59:52|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:59:52|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:00:10|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:05:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 18:05:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 18:05:17|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 18:05:17|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 18:05:17|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:05:17|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 18:05:17|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:05:19|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:10:21|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.40509140794165 -[06-21 18:10:21|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 18:10:22|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 -[06-21 18:10:22|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 18:10:22|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 18:10:23|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.json b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.json deleted file mode 100644 index 5ad5fef55e6eb614160097598925596a8aa1cf03..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_Building_2b_step35_masked_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.mp4 deleted file mode 100644 index a0fdcd2734fb8434825e32cd278a05d406d8611e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:f9024ee5875c84f49e57b6c08429506deafe64e897f36906aab05140c67de24f -size 1989333 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.txt b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.txt deleted file mode 100644 index 213c470aee0671b5a985429e153c07e4efd43cd3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 661f05d3d84639390886cf08f68fccc8a521abbd..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/rainy_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:4652cd6747cb16aa088fd9020af5cc1d755e71f2d3864adac7f14133197fad5c -size 1330422 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/spec.json b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/spec.json deleted file mode 100644 index 1e29bcd6032d409e3b5958a7fd297bfbb808b2c7..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.1_rm1/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "rainy_Building_2b_step35_masked_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/config.yaml b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/config.yaml deleted file mode 100644 index 09962d5e23551ab7cbcedca2207ec1c35edbcfed..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/console.log b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/console.log deleted file mode 100644 index 68d90398d6bf75ae4311af75964b8f5e89b7e98b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 18:10:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 18:10:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 18:10:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 18:10:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 18:10:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 18:10:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 18:10:50|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 18:10:50|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 18:10:51|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/config.yaml -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_masked_bg0.5_rm1'] -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_masked_bg0.5_rm1 -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.json -[06-21 18:10:52|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 18:21:29|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 -[06-21 18:21:29|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 18:21:30|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/debug.log b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/debug.log deleted file mode 100644 index 94fde7aa34eb2a26a9311f4f2aba9720a9befbcd..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 18:10:26|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 18:10:27|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 18:10:27|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 18:10:38|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 18:10:38|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 18:10:39|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 18:10:39|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 18:10:39|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 18:10:39|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 18:10:39|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 18:10:39|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 18:10:39|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 18:10:39|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 18:10:39|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 18:10:39|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 18:10:39|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 18:10:39|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 18:10:39|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 18:10:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 18:10:40|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 18:10:40|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 18:10:40|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 18:10:40|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 18:10:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 18:10:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 18:10:41|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 18:10:41|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.13 s -[06-21 18:10:44|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 18:10:44|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:44|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.07 s -[06-21 18:10:45|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.83 s -[06-21 18:10:45|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.12 s -[06-21 18:10:45|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.12 s -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 18:10:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 18:10:45|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 18:10:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 18:10:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 18:10:46|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 18:10:46|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 18:10:46|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 18:10:46|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 18:10:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 18:10:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 18:10:50|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 18:10:50|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 18:10:50|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 18:10:50|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.01 s -[06-21 18:10:50|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 18:10:50|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 18:10:50|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 18:10:51|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 18:10:51|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 18:10:51|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 18:10:51|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 18:10:51|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 18:10:51|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/config.yaml -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_2b_step35_masked_bg0.5_rm1'] -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_2b_step35_masked_bg0.5_rm1 -[06-21 18:10:52|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_Building_2b_step35_masked_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.json -[06-21 18:10:52|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 18:10:52|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4 -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4 -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 18:10:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 18:10:53|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 18:10:53|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 18:10:53|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:10:53|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 18:10:53|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:11:11|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:16:20|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 18:16:20|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 18:16:20|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 18:16:21|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 18:16:21|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:16:21|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 18:16:21|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:16:23|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 18:21:26|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 315.8466118169017 -[06-21 18:21:27|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 18:21:29|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 -[06-21 18:21:29|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 18:21:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 18:21:30|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.json b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.json deleted file mode 100644 index 7f39605f793e10d68e90b627f5f77a7e347c34fd..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_Building_2b_step35_masked_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.mp4 deleted file mode 100644 index 1c686cdb6e2c3da61df8c867f90522a448b26af4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:4feeb1b228d41c0afc56c0f04fcb8faffe4273155167ab2007be3bca1cf687c9 -size 2158600 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.txt b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.txt deleted file mode 100644 index 213c470aee0671b5a985429e153c07e4efd43cd3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index b9c8b1639dd4bb87fbb62c607b04c3c10bc6fe35..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/rainy_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:3ccc17ad8d0fcf8b7eb0dbca809b11fd46d91ffb5fedcf75e938a67ecad824c4 -size 1334068 diff --git a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/spec.json b/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/spec.json deleted file mode 100644 index dbbd06a86eb12e7c1fd1e7dfbd1ef5e242904e88..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/2b_step35_masked_bg0.5_rm1/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "rainy_Building_2b_step35_masked_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/Building_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/config.yaml deleted file mode 100644 index ff4470f323e0ba016001d19201174fae73ef55ed..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/console.log b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/console.log deleted file mode 100644 index c9ee8c0be1aa37cdf2246bb7fde2a533e8c68adc..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 17:06:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 17:06:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 17:06:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:06:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:06:15|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:06:15|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:06:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:06:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:06:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 17:06:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/config.yaml -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_distilled_step4_bg0.1_rm0.5'] -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_distilled_step4_bg0.1_rm0.5 -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.json -[06-21 17:06:52|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:08:02|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 17:08:03|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 -[06-21 17:08:03|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:08:04|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/debug.log b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/debug.log deleted file mode 100644 index 0f5cdb3eb30b591efab84c7c1f06de510aaa40b2..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 17:05:56|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 17:05:58|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:05:58|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:06:11|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:06:11|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:06:11|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 17:06:12|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 17:06:12|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 17:06:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 17:06:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 17:06:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 17:06:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 17:06:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 17:06:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 17:06:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 17:06:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 17:06:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 17:06:12|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 17:06:12|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 17:06:12|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 17:06:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 17:06:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 17:06:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 17:06:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 17:06:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 17:06:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 17:06:14|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 17:06:14|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 17:06:14|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 17:06:14|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 17:06:14|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 17:06:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:06:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:06:15|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 17:06:15|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 17:06:15|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 17:06:15|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 17:06:15|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:06:15|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:06:24|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 17:06:24|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 17:06:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:06:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:06:25|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:25|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.80 s -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 17:06:26|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 17:06:26|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 17:06:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 12.43 s -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:06:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:06:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:06:27|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 17:06:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 17:06:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:06:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:06:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:06:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 17:06:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 17:06:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 17:06:28|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 17:06:28|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 13.89 s -[06-21 17:06:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 17:06:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 17:06:28|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 17:06:52|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 17:06:52|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:06:52|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:06:52|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 17:06:52|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 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'control_blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'control_blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'control_blocks.3._checkpoint_wrapped_module.after_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.after_proj.bias'], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 17:06:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/config.yaml -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_distilled_step4_bg0.1_rm0.5'] -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_distilled_step4_bg0.1_rm0.5 -[06-21 17:06:52|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_Building_distilled_step4_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.json -[06-21 17:06:52|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:06:52|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:06:52|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 17:06:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 17:06:52|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:06:53|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 17:06:53|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 17:06:53|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 17:06:53|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 17:06:53|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4 -[06-21 17:06:53|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 176 -[06-21 17:06:53|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 17:06:53|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 17:07:33|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 17:07:34|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 17:08:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 33.32103759062011 -[06-21 17:08:02|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 17:08:02|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:08:03|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 -[06-21 17:08:03|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:08:03|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:08:04|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.json b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.json deleted file mode 100644 index 1e60c06ab7a6d1fa47ecd39f4033fe77d3932ff3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_Building_distilled_step4_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.mp4 b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.mp4 deleted file mode 100644 index d3850b8e6968576779f0ecd48e4889c116b0c997..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:27c3787109a281e8b4d0b2e4df7f4baf76c66795ecd5429018c921b2dc179f07 -size 2228255 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.txt b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.txt deleted file mode 100644 index 213c470aee0671b5a985429e153c07e4efd43cd3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 0efd7167248d6dc726173bc526b89fbe81ff601c..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/rainy_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:7485b050e777b96bed1aa6964ab1403dcc5f780868ddb049bf7c86e10fb761ef -size 1676430 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/spec.json b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/spec.json deleted file mode 100644 index d652538b44b87b5b6e60d87e31cd367b33bfb900..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_Building_distilled_step4_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/config.yaml b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/config.yaml deleted file mode 100644 index ac479f4044ec7828889be02526b4190d34c65d4b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/console.log b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/console.log deleted file mode 100644 index ce04d93a47cdc2d1f1203675a08acf58939063d3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 17:08:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 17:08:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 17:08:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:08:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:08:22|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:08:22|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:08:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:08:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:08:29|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 17:08:29|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/config.yaml -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_distilled_step4_bg0.1_rm1'] -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_distilled_step4_bg0.1_rm1 -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.json -[06-21 17:08:30|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:09:36|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 17:09:37|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 -[06-21 17:09:37|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:09:39|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/debug.log b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/debug.log deleted file mode 100644 index cfbd8d0bb383777be7f7f2b1b1ec97438b8e43d2..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 17:08:07|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 17:08:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:08:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:08:19|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:08:19|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:08:20|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 17:08:20|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 17:08:20|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 17:08:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 17:08:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 17:08:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 17:08:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 17:08:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 17:08:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 17:08:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 17:08:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 17:08:20|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 17:08:20|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 17:08:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 17:08:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 17:08:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 17:08:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 17:08:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 17:08:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 17:08:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 17:08:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 17:08:21|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 17:08:21|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 17:08:21|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 17:08:21|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 17:08:21|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 17:08:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:08:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:08:22|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 17:08:22|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 17:08:22|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 17:08:22|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 17:08:22|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:08:22|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:08:26|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 17:08:26|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 17:08:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:08:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 17:08:27|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 17:08:27|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 17:08:27|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 6.45 s -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:08:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:08:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:08:28|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 17:08:28|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 17:08:28|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:08:28|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:08:28|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:08:28|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 17:08:28|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 17:08:28|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 17:08:28|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 17:08:29|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 7.79 s -[06-21 17:08:29|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 17:08:29|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 17:08:29|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 17:08:30|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 17:08:30|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.5.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:08:30|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:08:30|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 17:08:30|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 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'control_blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'control_blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'control_blocks.3._checkpoint_wrapped_module.after_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.after_proj.bias'], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 17:08:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/config.yaml -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_distilled_step4_bg0.1_rm1'] -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_distilled_step4_bg0.1_rm1 -[06-21 17:08:30|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_Building_distilled_step4_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.json -[06-21 17:08:30|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:08:30|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:08:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 17:08:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 17:08:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:08:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 17:08:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 17:08:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 17:08:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 17:08:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4 -[06-21 17:08:31|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:08:31|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 17:08:31|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 17:09:08|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 17:09:08|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 17:09:36|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.734097709995694 -[06-21 17:09:36|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 17:09:36|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:09:37|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 -[06-21 17:09:37|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:09:38|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:09:39|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.json b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.json deleted file mode 100644 index 0e1fc86c2ca1f03e95c80081dd55c78904043abd..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_Building_distilled_step4_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.mp4 b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.mp4 deleted file mode 100644 index 96e7983407dfb9a8680dbcf269ceb53412b19015..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:3eb80825fe9ff6bfe5a72d283ccf8723b5b0bc6d4ad40f5aa3f22a7119bcfce1 -size 4298811 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.txt b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.txt deleted file mode 100644 index 213c470aee0671b5a985429e153c07e4efd43cd3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 3d26387ac3b10e58e0ccf5d217c25453be731eef..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/rainy_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:dc0a0df691bf27491874ae8aa19c94186b1824969467acc8e5ec0befdad2d3db -size 2163198 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/spec.json b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/spec.json deleted file mode 100644 index 3ad99b5ac77ce9a0ee7b800716543e081101b762..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.1_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_Building_distilled_step4_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/config.yaml b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/config.yaml deleted file mode 100644 index d63f330d908c2fb2cd9c5b42e57656be86bea405..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/console.log b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/console.log deleted file mode 100644 index 0b4acc32e74c6a5e0ffd1b5fb7f85423da076746..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 17:09:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 17:09:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 17:09:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:09:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:09:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:09:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:10:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:10:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:10:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 17:10:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/config.yaml -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_distilled_step4_bg0.5_rm1'] -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_distilled_step4_bg0.5_rm1 -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.json -[06-21 17:10:05|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:11:11|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 17:11:12|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 -[06-21 17:11:12|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:11:13|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/debug.log b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/debug.log deleted file mode 100644 index c8092182813555bbf4dd62e9aa27c136e379c997..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 17:09:42|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 17:09:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:09:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 17:09:54|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:09:54|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 17:09:54|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 17:09:54|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 17:09:54|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 17:09:55|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 17:09:55|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 17:09:55|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 17:09:55|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 17:09:55|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 17:09:55|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 17:09:55|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 17:09:55|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 17:09:55|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 17:09:55|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 17:09:55|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 17:09:55|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 17:09:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 17:09:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 17:09:55|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 17:09:55|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 17:09:55|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 17:09:55|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 17:09:56|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 17:09:56|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 17:09:56|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 17:09:56|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 17:09:56|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 17:09:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 17:09:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:09:56|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 17:09:56|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 17:09:56|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 17:09:56|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 17:09:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 17:09:56|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 17:10:00|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 17:10:00|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 17:10:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 17:10:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 17:10:01|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 17:10:02|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 17:10:02|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 17:10:02|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 6.40 s -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:10:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 17:10:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 17:10:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 17:10:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:10:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:10:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 17:10:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 17:10:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 17:10:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 17:10:03|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 17:10:03|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 7.73 s -[06-21 17:10:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 17:10:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 17:10:04|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 17:10:04|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 17:10:04|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 17:10:04|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:10:04|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 17:10:05|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 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'control_blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'control_blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'control_blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'control_blocks.3._checkpoint_wrapped_module.after_proj.weight', 'control_blocks.3._checkpoint_wrapped_module.after_proj.bias'], unexpected_keys=[], incorrect_shapes=[]) -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/config.yaml -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_Building_distilled_step4_bg0.5_rm1'] -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_Building_distilled_step4_bg0.5_rm1 -[06-21 17:10:05|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_Building_distilled_step4_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.json -[06-21 17:10:05|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 17:10:05|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4 -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 17:10:05|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 17:10:43|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 17:10:43|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 17:11:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.690547431469895 -[06-21 17:11:11|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 17:11:11|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:11:12|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 -[06-21 17:11:12|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:11:12|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:11:13|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.json b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.json deleted file mode 100644 index 33196f8c2e4bec4d7ee53e18bb12f8bbf3b14fb2..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_Building_distilled_step4_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.mp4 b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.mp4 deleted file mode 100644 index 3d36d1945ea08e1bddda9d5ef4baa5d90bc533b6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:f51a3443ded67965b1f7c66dfe81692501cd8b6b1ba508ea4614eb695f5e117e -size 4045339 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.txt b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.txt deleted file mode 100644 index 213c470aee0671b5a985429e153c07e4efd43cd3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index 5fc5f4b057f706d7a54074ed1ded7dfa297ca3fb..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/rainy_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:c49968d42faa0f81106ab6e92fceb2d588c040f9c4603f3d5822f112aa2bddeb -size 2200693 diff --git a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/spec.json b/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/spec.json deleted file mode 100644 index d0dbb5ac4df6d876f7d62064a9f83054ff4523ca..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/Building/distilled_step4_bg0.5_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_Building_distilled_step4_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a rainy overcast day. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades darkened and glistening from the rain. A wet road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft diffuse overcast light, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/config.yaml deleted file mode 100644 index 9c6c75e4cebddb07b91db473647050869276ba07..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/console.log b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/console.log deleted file mode 100644 index c0050ff4fd1ed17c105c7c1003eb96495c1d6fcd..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 15:48:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:48:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:49:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 15:49:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/config.yaml -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_bg0.1_rm0.5'] -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_bg0.1_rm0.5 -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.json -[06-21 15:49:06|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 15:59:39|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 -[06-21 15:59:39|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:59:41|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/debug.log b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/debug.log deleted file mode 100644 index 766503f72bb034cc9151c0264fcba209993fd6ba..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 15:48:41|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 15:48:42|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:48:42|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:48:52|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:48:53|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:48:53|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 15:48:53|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 15:48:53|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 15:48:53|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 15:48:53|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 15:48:53|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 15:48:53|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 15:48:53|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 15:48:53|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 15:48:53|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 15:48:54|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 15:48:54|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 15:48:54|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 15:48:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 15:48:54|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:48:54|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 15:48:54|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:48:54|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 15:48:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:48:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:48:55|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 15:48:55|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 0.98 s -[06-21 15:48:59|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:48:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.33 s -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.33 s -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 15:49:00|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 15:49:00|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:49:00|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 15:49:00|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 15:49:00|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:49:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:49:04|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 15:49:04|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 15:49:04|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:49:04|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.14 s -[06-21 15:49:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 15:49:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:49:05|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:49:06|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:49:06|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 15:49:06|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 15:49:06|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 15:49:06|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/config.yaml -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_bg0.1_rm0.5'] -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_bg0.1_rm0.5 -[06-21 15:49:06|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_weather_2b_step35_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.json -[06-21 15:49:06|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:49:06|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 15:49:06|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 15:49:06|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 15:49:06|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4 -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 176 -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 15:49:07|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:49:07|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 15:49:07|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:49:25|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:54:33|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 15:54:33|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 15:54:33|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 15:54:33|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 15:54:33|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:54:33|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 15:54:33|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:54:35|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:59:38|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 314.55199037049897 -[06-21 15:59:38|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:59:39|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 -[06-21 15:59:39|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:59:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:59:41|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.json b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.json deleted file mode 100644 index 83aefc086238d5034dc21cf33ecc037711f0eca1..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_weather_2b_step35_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.mp4 deleted file mode 100644 index 5d2114103392425c4b47fbb39f05f66e74bfce70..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:65b1397a6f316f4d1f290abec4c763eb0c7efe7daa399d8269246da089653d2c -size 2423437 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.txt b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.txt deleted file mode 100644 index 4987ef5fda9ebef26e8337960223fe1a39f70c28..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 0efd7167248d6dc726173bc526b89fbe81ff601c..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/rainy_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:7485b050e777b96bed1aa6964ab1403dcc5f780868ddb049bf7c86e10fb761ef -size 1676430 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/spec.json b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/spec.json deleted file mode 100644 index 4db8cc8b57f0928d5063394678f0ede58e96ebdf..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_weather_2b_step35_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/config.yaml b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/config.yaml deleted file mode 100644 index 4661421c6a6d729b2a6454198d3f4e415e543938..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/console.log b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/console.log deleted file mode 100644 index a3e038702b1c9d5db760a51245d792eb4cffa619..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 15:59:58|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:59:58|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 16:00:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:00:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:00:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:00:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:00:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:00:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/config.yaml -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_bg0.1_rm1'] -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_bg0.1_rm1 -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.json -[06-21 16:00:10|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 16:11:03|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1_control_edge.mp4 -[06-21 16:11:03|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 16:11:05|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/debug.log b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/debug.log deleted file mode 100644 index fb3e661cc6b1cc8740f8b09bdb8de363e30cd0fe..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 15:59:44|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 15:59:45|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:59:45|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:59:56|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:59:57|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:59:57|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 15:59:57|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 15:59:57|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 15:59:57|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 15:59:57|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 15:59:57|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 15:59:57|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 15:59:57|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 15:59:57|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 15:59:57|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 15:59:57|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 15:59:57|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 15:59:57|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 15:59:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 15:59:58|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:59:58|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 15:59:58|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:59:58|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 15:59:58|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:59:58|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:59:59|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 15:59:59|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.29 s -[06-21 16:00:02|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 16:00:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 16:00:03|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 16:00:03|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.10 s -[06-21 16:00:03|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.10 s -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 16:00:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 16:00:03|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 16:00:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:00:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:00:04|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 16:00:04|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 16:00:04|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 16:00:04|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 16:00:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:00:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:00:08|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 16:00:08|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 16:00:08|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 16:00:08|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.22 s -[06-21 16:00:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:00:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:00:09|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:00:09|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.24.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:00:10|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 16:00:10|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 16:00:10|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/config.yaml -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_bg0.1_rm1'] -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_bg0.1_rm1 -[06-21 16:00:10|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_weather_2b_step35_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.json -[06-21 16:00:10|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:00:10|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4 -[06-21 16:00:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:00:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 16:00:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 16:00:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 16:00:11|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 16:00:11|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:00:11|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 16:00:11|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:00:29|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:05:46|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 16:05:46|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 16:05:47|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 16:05:48|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 16:05:48|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:05:48|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 16:05:48|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:05:50|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:11:00|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 319.77580696798395 -[06-21 16:11:01|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 16:11:03|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1_control_edge.mp4 -[06-21 16:11:03|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 16:11:03|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 16:11:05|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.json b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.json deleted file mode 100644 index 1e13f50a235e196676f9dbc8324a5e1721558106..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_weather_2b_step35_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.mp4 deleted file mode 100644 index c01ba97f919ff9e309a4e6ed35594cb655cbdf46..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:420db7d61db08aec56f952b959717e6a139ea92c26ef42a4e2e0299ce540c2a3 -size 5874957 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.txt b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.txt deleted file mode 100644 index 4987ef5fda9ebef26e8337960223fe1a39f70c28..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 3d26387ac3b10e58e0ccf5d217c25453be731eef..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/rainy_weather_2b_step35_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:dc0a0df691bf27491874ae8aa19c94186b1824969467acc8e5ec0befdad2d3db -size 2163198 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/spec.json b/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/spec.json deleted file mode 100644 index a021b6d494863d6307d8f4592ccefd2ff1c13705..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.1_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_weather_2b_step35_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/config.yaml b/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/config.yaml deleted file mode 100644 index 2f14a9144b03cb0bfe808e37116a14f468a3ca06..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/console.log b/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/console.log deleted file mode 100644 index ffd68f6d9bac3d8199b148ec5c19ff560893547d..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 16:14:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 16:14:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 16:15:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:15:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:15:15|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:15:15|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:15:19|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:15:19|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/config.yaml -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_bg0.5_rm1'] -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_bg0.5_rm1 -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.json -[06-21 16:15:21|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 16:26:09|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1_control_edge.mp4 -[06-21 16:26:09|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 16:26:10|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/debug.log b/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/debug.log deleted file mode 100644 index a875f9f3d960ab0fecb11c09ce23ebfa8389ee69..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 16:11:59|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 16:12:16|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 16:12:16|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 16:14:21|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 16:14:30|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 16:14:38|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 16:14:40|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 16:14:40|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 16:14:40|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 16:14:40|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 16:14:40|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 16:14:40|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 16:14:40|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 16:14:40|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 16:14:40|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 16:14:41|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 16:14:42|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 16:14:43|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 16:14:43|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 16:14:43|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 16:14:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 16:14:43|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 16:14:43|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 16:14:44|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 16:14:44|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 16:14:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 16:14:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 16:14:54|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 16:14:55|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 11.04 s -[06-21 16:14:58|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:14:58|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:58|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:14:59|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 8.38 s -[06-21 16:15:07|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 9.15 s -[06-21 16:15:07|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 12.41 s -[06-21 16:15:07|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 12.41 s -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 16:15:07|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 16:15:07|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 16:15:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:15:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:15:08|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 16:15:08|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 16:15:08|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 16:15:15|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 16:15:15|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:15:15|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:15:19|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 16:15:19|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 16:15:19|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 16:15:19|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 35.78 s -[06-21 16:15:19|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:15:19|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:15:20|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:15:21|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:15:21|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 16:15:21|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 16:15:21|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 16:15:21|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/config.yaml -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_bg0.5_rm1'] -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_bg0.5_rm1 -[06-21 16:15:21|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_weather_2b_step35_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.json -[06-21 16:15:21|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:15:21|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 16:15:21|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 16:15:21|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 16:15:25|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:15:26|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 16:15:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 16:15:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 16:15:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 16:15:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 16:15:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4 -[06-21 16:15:38|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:15:38|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 16:15:38|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 16:15:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 16:15:38|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 16:15:38|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:15:38|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 16:15:38|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:15:56|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:21:03|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 16:21:03|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 16:21:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 16:21:03|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 16:21:03|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:21:03|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 16:21:03|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:21:05|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:26:08|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.92758178152144 -[06-21 16:26:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 16:26:09|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1_control_edge.mp4 -[06-21 16:26:09|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 16:26:09|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 16:26:10|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.json b/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.json deleted file mode 100644 index c9970f44bf806fc28c1433b90178706c0e3571d0..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_weather_2b_step35_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.mp4 deleted file mode 100644 index 974638b09c2eec497ecac3476732110debf610b6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:694d912d3e9fc546ec2329374a66488b973825788b00834d8f4a2476dec403c7 -size 5946871 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.txt b/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.txt deleted file mode 100644 index 4987ef5fda9ebef26e8337960223fe1a39f70c28..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index 5fc5f4b057f706d7a54074ed1ded7dfa297ca3fb..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/rainy_weather_2b_step35_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:c49968d42faa0f81106ab6e92fceb2d588c040f9c4603f3d5822f112aa2bddeb -size 2200693 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/spec.json b/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/spec.json deleted file mode 100644 index 527f9c46129d8f662ab8803405cb066cb5802d8a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_bg0.5_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_weather_2b_step35_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml deleted file mode 100644 index 315f9c46563ea86f810229bb88c8dedd0cf7765f..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/console.log b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/console.log deleted file mode 100644 index 30522e414bb73cf911ebd9b6e50511fd6f2a20e3..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 16:26:34|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 16:26:34|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 16:26:39|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:26:39|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:26:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:26:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:26:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:26:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:26:45|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_masked_bg0.1_rm0.5'] -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_masked_bg0.1_rm0.5 -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.json -[06-21 16:26:46|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 16:37:18|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 -[06-21 16:37:18|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 16:37:19|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/debug.log b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/debug.log deleted file mode 100644 index 4e896bed1dab5f871b8ef865f5b6041e8e8fb851..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 16:26:20|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 16:26:21|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 16:26:21|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 16:26:32|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 16:26:33|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 16:26:33|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 16:26:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 16:26:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 16:26:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 16:26:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 16:26:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 16:26:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 16:26:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 16:26:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 16:26:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 16:26:33|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 16:26:33|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 16:26:33|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 16:26:33|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 16:26:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 16:26:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 16:26:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 16:26:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 16:26:34|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 16:26:34|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 16:26:34|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 16:26:34|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 16:26:34|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 16:26:34|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 16:26:35|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 16:26:35|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.04 s -[06-21 16:26:38|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 16:26:38|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:38|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 16:26:39|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 16:26:39|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.09 s -[06-21 16:26:39|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.09 s -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 16:26:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 16:26:39|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 16:26:39|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:26:39|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:26:40|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 16:26:40|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 16:26:40|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 16:26:40|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 16:26:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:26:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:26:44|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 16:26:44|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 16:26:44|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 16:26:44|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 9.92 s -[06-21 16:26:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:26:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:26:44|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:26:45|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:26:45|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 16:26:45|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 16:26:45|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 16:26:45|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 16:26:45|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_masked_bg0.1_rm0.5'] -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_masked_bg0.1_rm0.5 -[06-21 16:26:46|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_weather_2b_step35_masked_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.json -[06-21 16:26:46|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:26:46|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4 -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 176 -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4 -[06-21 16:26:46|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:26:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 16:26:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 16:26:47|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 16:26:47|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 16:26:47|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:26:47|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 16:26:47|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:27:05|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:32:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 16:32:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 16:32:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 16:32:12|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 16:32:12|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:32:12|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 16:32:12|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:32:14|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:37:17|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 314.02611197403166 -[06-21 16:37:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 16:37:18|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 -[06-21 16:37:18|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 16:37:18|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 16:37:19|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.json b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.json deleted file mode 100644 index 6747d7369d74d4abde8b6040ec77e80b2e21bd4a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_weather_2b_step35_masked_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.mp4 deleted file mode 100644 index 52366ba447998ecb10a12d3ddd57b6314976c9da..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:b6ba3ae23c0df386b15d2cde6454f5d26724917cbbf110cefb9ec92b1a4fb933 -size 2458668 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.txt b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.txt deleted file mode 100644 index 4987ef5fda9ebef26e8337960223fe1a39f70c28..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 74c95e041760d95a2a6cab852fa4c0d184dbbf2e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/rainy_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:21c993048b39e7fe31a16ba7a7890c3602dbb128fda23152775cfaa05849ae57 -size 2385039 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/spec.json b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/spec.json deleted file mode 100644 index 3dbc10dc0220a150d2fb2578d9ceb505d24ec77d..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "rainy_weather_2b_step35_masked_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/config.yaml b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/config.yaml deleted file mode 100644 index 156c9dc54cabf3d23486b045c27607e1d4e5f90d..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/console.log b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/console.log deleted file mode 100644 index a113d2f53ce0d8f56e709695f653d0286f8b7951..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 16:37:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 16:37:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 16:37:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:37:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:37:57|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:37:57|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:38:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:38:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/config.yaml -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_masked_bg0.1_rm1'] -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_masked_bg0.1_rm1 -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.json -[06-21 16:38:10|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 16:49:06|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 -[06-21 16:49:06|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 16:49:08|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/debug.log b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/debug.log deleted file mode 100644 index d002a72fb584ecd5ab972d42de06254143b5d5ac..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 16:37:25|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 16:37:27|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 16:37:27|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 16:37:45|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 16:37:45|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 16:37:46|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 16:37:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 16:37:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 16:37:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 16:37:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 16:37:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 16:37:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 16:37:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 16:37:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 16:37:46|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 16:37:46|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 16:37:46|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 16:37:46|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 16:37:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 16:37:46|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 16:37:47|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 16:37:47|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 16:37:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 16:37:47|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 16:37:47|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 16:37:47|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 16:37:47|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 16:37:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 16:37:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 16:37:50|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 16:37:50|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 3.18 s -[06-21 16:37:54|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:37:54|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:54|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.12 s -[06-21 16:37:55|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 1.11 s -[06-21 16:37:55|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.85 s -[06-21 16:37:55|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.85 s -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 16:37:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 16:37:55|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 16:37:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:37:55|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:37:57|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 16:37:57|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 16:37:57|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 16:37:57|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 16:37:57|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:37:57|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:38:04|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 16:38:04|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 16:38:04|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 16:38:04|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 17.11 s -[06-21 16:38:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:38:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:38:05|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:38:10|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:38:10|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 16:38:10|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 16:38:10|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 16:38:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/config.yaml -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_masked_bg0.1_rm1'] -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_masked_bg0.1_rm1 -[06-21 16:38:10|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_weather_2b_step35_masked_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.json -[06-21 16:38:10|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:38:10|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 16:38:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 16:38:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 16:38:11|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:38:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 16:38:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 16:38:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 16:38:11|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 16:38:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 16:38:11|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4 -[06-21 16:38:12|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:38:12|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4 -[06-21 16:38:12|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:38:12|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 16:38:12|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 16:38:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 16:38:12|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 16:38:12|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:38:12|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 16:38:12|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:38:30|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:43:57|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 16:43:57|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 16:43:57|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 16:43:57|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 16:43:57|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:43:57|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 16:43:57|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:44:00|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:49:04|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 324.30879262648523 -[06-21 16:49:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 16:49:06|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 -[06-21 16:49:06|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 16:49:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 16:49:08|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.json b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.json deleted file mode 100644 index 3e0688f1737dfdc3a2939cc5c3a2014cfaeec810..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_weather_2b_step35_masked_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.mp4 deleted file mode 100644 index 373f5b93f7e2a3b6b758cf24a5a17fcc44f29e22..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:3102c4e0c086c8d28e456cd9947c209b7e9a9055325b9dd238eb408260bfd107 -size 5346513 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.txt b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.txt deleted file mode 100644 index 4987ef5fda9ebef26e8337960223fe1a39f70c28..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 2f8a51f41ee28fc2e396bc59dd3f20c1f9bf01ca..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/rainy_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:ef166b9bb6f5a94282405edc59d9b86b855367b9740ab33232b9fe75caf9282b -size 2952158 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/spec.json b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/spec.json deleted file mode 100644 index 232448ea2d5bdbae135a475a47ec06b8ccbe6c85..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.1_rm1/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "rainy_weather_2b_step35_masked_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/config.yaml b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/config.yaml deleted file mode 100644 index c818d238b065ec77ac2b76b8a9ade990b0d53e05..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/console.log b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/console.log deleted file mode 100644 index 486f9420fa68434a3a96b0afc27f3a7b936c8439..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 16:51:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 16:51:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 16:54:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:54:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:54:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:54:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:54:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:54:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/config.yaml -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_masked_bg0.5_rm1'] -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_masked_bg0.5_rm1 -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.json -[06-21 16:54:54|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 17:05:43|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 -[06-21 17:05:43|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:05:45|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/debug.log b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/debug.log deleted file mode 100644 index a90ede452db7c7dcd847923020140a61d05315a1..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 16:50:15|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 16:50:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 16:50:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 16:51:04|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 16:51:08|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 16:51:10|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 16:51:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 16:51:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 16:51:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 16:51:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 16:51:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 16:51:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 16:51:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 16:51:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 16:51:12|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 16:51:13|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 16:51:13|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 16:51:13|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 16:51:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 16:51:14|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 16:51:14|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 16:51:14|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 16:51:14|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 16:51:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 16:51:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 16:51:20|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 16:51:20|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 5.55 s -[06-21 16:54:29|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 16:54:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.10 s -[06-21 16:54:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.86 s -[06-21 16:54:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 190.51 s -[06-21 16:54:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 190.51 s -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 16:54:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 16:54:30|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 16:54:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 16:54:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:54:31|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 16:54:31|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 16:54:31|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 16:54:31|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 16:54:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 16:54:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 16:54:52|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 16:54:52|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 16:54:52|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 16:54:52|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 217.85 s -[06-21 16:54:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 16:54:52|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:54:52|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 16:54:53|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.22.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:53|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 16:54:54|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 16:54:54|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 16:54:54|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 16:54:54|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/config.yaml -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_2b_step35_masked_bg0.5_rm1'] -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_2b_step35_masked_bg0.5_rm1 -[06-21 16:54:54|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_weather_2b_step35_masked_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.json -[06-21 16:54:54|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 16:54:54|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 16:54:54|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 16:54:54|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 16:54:54|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:54:54|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4 -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4 -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 16:54:58|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 16:54:59|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:54:59|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 16:54:59|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 16:55:22|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:00:36|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 17:00:36|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 17:00:36|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 17:00:36|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 17:00:37|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:00:37|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 17:00:37|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:00:39|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 17:05:41|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 320.4878688520985 -[06-21 17:05:42|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:05:43|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 -[06-21 17:05:43|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 17:05:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 17:05:45|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.json b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.json deleted file mode 100644 index 7449a8896aa422c4dc958aef47fb25cfb8014b63..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_weather_2b_step35_masked_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.mp4 deleted file mode 100644 index 57cad71f33cc1c43dcfebde11570985c06e14871..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:24a07471c0e4209aa10f3417e68e41a9ad842d817db1e846569f7c2561995b4c -size 5389016 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.txt b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.txt deleted file mode 100644 index 4987ef5fda9ebef26e8337960223fe1a39f70c28..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index a2b297f3b6946d2d3beb17949ea8c440bebcaa32..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/rainy_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:f381091ce1ea9ef70f407146fed6e806517968bc2c757d6e7f88b9ca55a61a5e -size 3081104 diff --git a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/spec.json b/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/spec.json deleted file mode 100644 index 4a23f5b16bae2bc78844ccbc1c84418f6889ebf1..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/2b_step35_masked_bg0.5_rm1/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "rainy_weather_2b_step35_masked_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/rainy/weather_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/config.yaml deleted file mode 100644 index e18bae99d092dc13ecae0e5b74935e0d32437a45..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/console.log b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/console.log deleted file mode 100644 index 5cae1a7005153a1cd1f6d5f11cb1b9dce0f57e0f..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 15:42:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 15:42:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 15:42:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:42:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:42:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:42:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:43:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:43:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:43:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 15:43:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/config.yaml -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_distilled_step4_bg0.1_rm0.5'] -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_distilled_step4_bg0.1_rm0.5 -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.json -[06-21 15:43:33|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 15:44:39|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 15:44:41|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 -[06-21 15:44:41|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:44:42|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/debug.log b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/debug.log deleted file mode 100644 index 626c18c230e23ea7f40cab459904acc61c2d39a4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 15:42:30|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 15:42:31|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:42:31|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:42:41|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:42:42|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:42:42|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 15:42:43|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 15:42:43|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 15:42:43|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 15:42:43|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 15:42:43|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 15:42:43|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 15:42:43|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 15:42:43|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 15:42:43|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 15:42:43|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 15:42:43|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 15:42:43|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 15:42:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 15:42:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 15:42:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 15:42:44|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 15:42:44|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 15:42:44|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 15:42:44|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 15:42:44|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 15:42:45|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 15:42:45|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 15:42:45|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 15:42:45|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 15:42:45|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 15:42:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:42:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:42:46|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 15:42:46|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 15:42:46|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 15:42:46|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 15:42:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:42:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:43:00|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 15:43:00|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 15:43:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:43:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:43:01|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:01|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.79 s -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 15:43:02|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 15:43:02|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 15:43:02|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 17.23 s -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:43:02|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:02|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:43:03|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:43:03|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 15:43:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 15:43:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:43:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:43:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:43:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 15:43:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 15:43:03|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 15:43:04|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 15:43:04|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 18.81 s -[06-21 15:43:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 15:43:04|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 15:43:04|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 15:43:32|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 15:43:32|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced 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blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:43:32|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 15:43:32|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 15:43:32|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.4._checkpoint_wrapped_module.cross_attn.q_proj.weight', 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['rainy_weather_distilled_step4_bg0.1_rm0.5'] -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_distilled_step4_bg0.1_rm0.5 -[06-21 15:43:33|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_weather_distilled_step4_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.json -[06-21 15:43:33|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:43:33|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 15:43:33|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 15:43:33|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 15:43:33|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:43:33|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 15:43:33|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 15:43:33|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 15:43:33|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 15:43:33|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4 -[06-21 15:43:34|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 176 -[06-21 15:43:34|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 15:43:34|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 15:44:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 15:44:12|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 15:44:39|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.96000795508735 -[06-21 15:44:39|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 15:44:40|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:44:41|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 -[06-21 15:44:41|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:44:41|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:44:42|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.json b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.json deleted file mode 100644 index e786af6cdcd331c238eff1c6c7ad3bf289ac5b37..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_weather_distilled_step4_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.mp4 b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.mp4 deleted file mode 100644 index f41f2ebb06fa47983306b1d9ee5ccf676dcab797..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e2bbb77f50ac1d5a7980fc51a413366b9c9d0f33074d2025176829411ddac83a -size 1836511 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.txt b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.txt deleted file mode 100644 index 4987ef5fda9ebef26e8337960223fe1a39f70c28..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 0efd7167248d6dc726173bc526b89fbe81ff601c..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/rainy_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:7485b050e777b96bed1aa6964ab1403dcc5f780868ddb049bf7c86e10fb761ef -size 1676430 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/spec.json b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/spec.json deleted file mode 100644 index c02fa3e5ab5ec8ed90a9c131016fc5121d9efaef..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_weather_distilled_step4_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/config.yaml b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/config.yaml deleted file mode 100644 index db8aafe0f73fe18395b5a186386ef818bc6362b4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/console.log b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/console.log deleted file mode 100644 index 85128ad7ff86bc80b2a1a034e1d68855df7f10fd..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 15:45:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 15:45:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 15:45:22|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:45:22|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:45:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:45:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:45:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 15:45:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/config.yaml -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_distilled_step4_bg0.1_rm1'] -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_distilled_step4_bg0.1_rm1 -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.json -[06-21 15:45:31|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 15:46:37|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 15:46:39|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 -[06-21 15:46:39|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:46:40|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/debug.log b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/debug.log deleted file mode 100644 index 06e3fcdfd6f193f5089519a9badd813bc4dfdc5a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 15:45:08|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 15:45:09|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:45:09|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:45:20|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:45:20|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:45:21|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 15:45:21|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 15:45:21|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 15:45:21|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 15:45:21|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 15:45:21|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 15:45:21|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 15:45:21|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 15:45:21|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 15:45:21|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 15:45:21|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 15:45:21|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 15:45:21|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 15:45:21|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 15:45:21|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 15:45:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 15:45:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 15:45:21|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 15:45:21|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 15:45:21|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 15:45:21|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 15:45:22|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 15:45:22|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 15:45:22|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 15:45:22|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 15:45:22|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 15:45:22|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:45:22|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:45:23|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 15:45:23|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 15:45:23|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 15:45:23|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 15:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:45:27|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 15:45:27|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 15:45:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:45:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:45:28|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.66 s -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 15:45:28|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 15:45:28|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 15:45:28|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 6.71 s -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:28|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:45:29|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:45:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 15:45:30|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 15:45:30|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:45:30|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:45:30|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:45:30|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 15:45:30|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 15:45:30|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 15:45:30|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 15:45:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 8.06 s -[06-21 15:45:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 15:45:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 15:45:30|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 15:45:31|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 15:45:31|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:45:31|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 15:45:31|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 15:45:31|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.4._checkpoint_wrapped_module.cross_attn.q_proj.weight', 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['rainy_weather_distilled_step4_bg0.1_rm1'] -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_distilled_step4_bg0.1_rm1 -[06-21 15:45:31|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_weather_distilled_step4_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.json -[06-21 15:45:31|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:45:31|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 15:45:31|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 15:45:31|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 15:45:32|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:45:32|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 15:45:32|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 15:45:32|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 15:45:32|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 15:45:32|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4 -[06-21 15:45:32|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:45:32|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 15:45:32|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 15:46:09|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 15:46:09|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 15:46:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.72594420646783 -[06-21 15:46:37|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 15:46:38|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:46:39|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 -[06-21 15:46:39|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:46:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:46:40|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.json b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.json deleted file mode 100644 index aba5c6f71e5c848722432345f66bdadf0e4b9936..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_weather_distilled_step4_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.mp4 b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.mp4 deleted file mode 100644 index 8b0b7d4d2ce5185b30e4f8d17c2ed75c35f923a7..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:f9079b3bed869e6d933ba03421a9acd2ff714c055bdf43d478cae7b61ed622de -size 3718448 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.txt b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.txt deleted file mode 100644 index 4987ef5fda9ebef26e8337960223fe1a39f70c28..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 3d26387ac3b10e58e0ccf5d217c25453be731eef..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/rainy_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:dc0a0df691bf27491874ae8aa19c94186b1824969467acc8e5ec0befdad2d3db -size 2163198 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/spec.json b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/spec.json deleted file mode 100644 index aaebc572eddca4b02a1b68a6305792c07b7db7c9..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.1_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_weather_distilled_step4_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.1_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/config.yaml b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/config.yaml deleted file mode 100644 index 7ee2ae1cfaca80274fb632935542fb8585c7e12c..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/console.log b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/console.log deleted file mode 100644 index 49ec3a9f53647f18a16bcc70f0384a0eca135d29..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 15:47:19|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 15:47:19|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 15:47:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:47:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:47:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:47:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:47:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:47:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:47:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 15:47:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/config.yaml -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['rainy_weather_distilled_step4_bg0.5_rm1'] -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_distilled_step4_bg0.5_rm1 -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.json -[06-21 15:47:29|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 15:48:35|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 15:48:36|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 -[06-21 15:48:36|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:48:38|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/debug.log b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/debug.log deleted file mode 100644 index dd54edcec2958ae81484dcd669c63fcbf25012cf..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 15:47:06|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 15:47:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:47:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:47:18|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:47:18|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:47:18|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 15:47:19|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 15:47:19|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 15:47:19|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 15:47:19|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 15:47:19|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 15:47:19|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 15:47:19|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 15:47:19|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 15:47:19|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 15:47:19|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 15:47:19|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 15:47:19|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 15:47:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 15:47:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 15:47:19|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 15:47:19|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 15:47:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 15:47:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 15:47:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 15:47:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 15:47:20|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 15:47:20|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 15:47:20|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 15:47:20|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 15:47:20|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 15:47:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:47:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:47:20|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 15:47:20|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 15:47:21|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 15:47:21|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 15:47:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:47:21|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:47:24|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 15:47:24|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 15:47:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:47:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:47:25|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.66 s -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 15:47:26|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 15:47:26|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 15:47:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 6.53 s -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:47:26|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:26|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:47:27|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:47:27|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.67 s -[06-21 15:47:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 15:47:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:47:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:47:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:47:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 15:47:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 15:47:27|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 15:47:27|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 15:47:28|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 7.89 s -[06-21 15:47:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 15:47:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 15:47:28|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 15:47:29|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 15:47:29|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.15.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.15.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.16.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.16.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:47:29|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 15:47:29|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 15:47:29|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.4._checkpoint_wrapped_module.cross_attn.q_proj.weight', 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['rainy_weather_distilled_step4_bg0.5_rm1'] -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample rainy_weather_distilled_step4_bg0.5_rm1 -[06-21 15:47:29|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='rainy_weather_distilled_step4_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.json -[06-21 15:47:29|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:47:29|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 15:47:29|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 15:47:29|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4 -[06-21 15:47:29|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:47:29|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 15:47:29|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 15:47:29|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 15:47:29|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 15:47:29|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4 -[06-21 15:47:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:47:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 15:47:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 15:48:07|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 15:48:07|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 15:48:35|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.71101951599121 -[06-21 15:48:35|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 15:48:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:48:36|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 -[06-21 15:48:36|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:48:36|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:48:38|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.json b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.json deleted file mode 100644 index 2e680b2b66033ad8793ca70c180b84b376ea9b39..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"rainy_weather_distilled_step4_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.mp4 b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.mp4 deleted file mode 100644 index e76e5787ab03228f64b195f71b8fe6fbd89ff67b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:c70638ad94d19c914c91783b004b76de5f1d2fa2c81fd3622d3672480bf72435 -size 3495441 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.txt b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.txt deleted file mode 100644 index 4987ef5fda9ebef26e8337960223fe1a39f70c28..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail. \ No newline at end of file diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index 5fc5f4b057f706d7a54074ed1ded7dfa297ca3fb..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/rainy_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:c49968d42faa0f81106ab6e92fceb2d588c040f9c4603f3d5822f112aa2bddeb -size 2200693 diff --git a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/spec.json b/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/spec.json deleted file mode 100644 index 4184f8728096fc563c754c4e0824cc0a1e81f206..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/rainy/weather/distilled_step4_bg0.5_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "rainy_weather_distilled_step4_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera during heavy rain. A flat overcast grey sky hangs low over the scene, the asphalt is dark, wet and mirror-like with rippling puddles and reflections of the surroundings, rain streaks the air and droplets bead on surfaces. The painted lane markings, stop lines and pedestrian crosswalks show through the glossy wet road. Multiple vehicles move through the junction with headlights on, low-rise buildings, sidewalks and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, moody overcast lighting, detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000_rainy/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/rainy/edge_bg0.5_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Bright sunlight, blue sky, dry road, hard crisp shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/config.yaml deleted file mode 100644 index efe863bc8ac89fdc9f4630d28cead77c3741889d..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/console.log b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/console.log deleted file mode 100644 index 316ccd348047ef47afe8cc3b45ac651cad1c82ef..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 14:34:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:34:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:34:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:34:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:34:41|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:34:41|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:34:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:34:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/config.yaml -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_bg0.1_rm0.5'] -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_bg0.1_rm0.5 -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.json -[06-21 14:34:47|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:45:17|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 -[06-21 14:45:17|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:45:19|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/debug.log b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/debug.log deleted file mode 100644 index 8be2ca6d028984fde3da735d2331d1a74a9580c4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 14:34:22|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 14:34:23|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:34:23|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:34:34|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:34:34|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:34:34|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 14:34:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 14:34:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 14:34:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 14:34:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 14:34:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 14:34:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 14:34:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 14:34:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 14:34:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 14:34:35|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 14:34:35|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 14:34:35|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 14:34:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 14:34:35|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:34:35|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 14:34:35|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:34:35|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 14:34:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:34:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:34:36|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 14:34:36|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 0.98 s -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 14:34:40|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 14:34:40|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.12 s -[06-21 14:34:40|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.12 s -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 14:34:40|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 14:34:40|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 14:34:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:34:40|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:34:41|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 14:34:41|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 14:34:41|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 14:34:41|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 14:34:41|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:34:41|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:34:45|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 14:34:45|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 14:34:45|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:34:45|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 9.86 s -[06-21 14:34:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:34:45|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:34:46|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:34:47|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:34:47|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 14:34:47|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 14:34:47|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/config.yaml -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_bg0.1_rm0.5'] -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_bg0.1_rm0.5 -[06-21 14:34:47|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_Building_2b_step35_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.json -[06-21 14:34:47|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:34:47|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4 -[06-21 14:34:47|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 179 -[06-21 14:34:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 14:34:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 14:34:48|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:34:48|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:34:48|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:34:48|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:34:48|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:35:06|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:40:12|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 14:40:12|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 14:40:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:40:12|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:40:12|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:40:12|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:40:12|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:40:15|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:45:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.3993654923979 -[06-21 14:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:45:17|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 -[06-21 14:45:17|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:45:18|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:45:19|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/spec.json b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/spec.json deleted file mode 100644 index 918ef3da4db213e977d8d66528a7a43a5fc39908..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_Building_2b_step35_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.json b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.json deleted file mode 100644 index 3e0ece63266be244f5fa14d9e8d4fbf3db0670c8..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_Building_2b_step35_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.mp4 deleted file mode 100644 index 322d5d29bff8713d6098a4d0531d53bdf33a3914..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:8360d68cbe9ee9d3129db76c01ec127dfeb68a93dee904b602667e0604ac421e -size 2181794 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.txt b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.txt deleted file mode 100644 index 20a963b13c72a11374e0cef9d7e75383860a19e6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 31517dea0588b3196cdefd6c05d01c13532f321a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm0.5/sunny_Building_2b_step35_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:82d37f9770a7b373f8f9fb16267abb84131023d9ecda8dcc622bb8cf91dbfb93 -size 1419864 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/config.yaml b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/config.yaml deleted file mode 100644 index da95c05177d024ed6ec702226d81e7df563dd9aa..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/console.log b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/console.log deleted file mode 100644 index 86b8f6a5cdd150f238a21c5b1f78a4700aa67ae0..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 14:45:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:45:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:45:41|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:45:41|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:45:42|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:45:42|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:45:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:45:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:45:47|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/config.yaml -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_bg0.1_rm1'] -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_bg0.1_rm1 -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.json -[06-21 14:45:48|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:56:20|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1_control_edge.mp4 -[06-21 14:56:20|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:56:22|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/debug.log b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/debug.log deleted file mode 100644 index 50f9106c1094056b2b7ee0c9cc447eb343242467..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 14:45:22|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 14:45:23|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:45:23|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:45:34|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:45:34|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:45:35|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 14:45:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 14:45:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 14:45:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 14:45:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 14:45:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 14:45:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 14:45:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 14:45:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 14:45:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 14:45:35|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 14:45:35|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 14:45:35|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 14:45:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 14:45:35|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:45:36|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 14:45:36|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:45:36|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 14:45:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:45:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:45:37|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 14:45:37|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.29 s -[06-21 14:45:40|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:45:40|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:45:40|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 14:45:41|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 14:45:41|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.13 s -[06-21 14:45:41|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.13 s -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 14:45:41|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 14:45:41|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 14:45:41|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:45:41|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:45:42|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 14:45:42|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 14:45:42|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 14:45:42|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 14:45:42|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:45:42|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:45:46|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 14:45:46|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 14:45:46|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:45:46|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.19 s -[06-21 14:45:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:45:46|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:45:46|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:45:47|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:45:47|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 14:45:47|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 14:45:47|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 14:45:47|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 14:45:47|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/config.yaml -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_bg0.1_rm1'] -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_bg0.1_rm1 -[06-21 14:45:48|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_Building_2b_step35_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.json -[06-21 14:45:48|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:45:48|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4 -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:45:48|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:45:48|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:45:48|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:46:06|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:51:13|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 14:51:13|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 14:51:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:51:13|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:51:13|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:51:13|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:51:13|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:51:15|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:56:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 314.0020832455484 -[06-21 14:56:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:56:20|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1_control_edge.mp4 -[06-21 14:56:20|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:56:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:56:22|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/spec.json b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/spec.json deleted file mode 100644 index 30c82c4533c5b9ce6479bfba646bf0f633a3a316..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_Building_2b_step35_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.json b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.json deleted file mode 100644 index 636cfff13fedfdc804d99b0d6e853dbc0beef359..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_Building_2b_step35_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.mp4 deleted file mode 100644 index 060139c27053b104b567677478324fa109e74c3c..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:9a4f7fd19177f547fcf7f8a8b814c23d57f2ed5e543d22c9ad9412a20ef7d7f8 -size 6531557 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.txt b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.txt deleted file mode 100644 index 20a963b13c72a11374e0cef9d7e75383860a19e6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 4e05a50fa2ad1e0a28d85922afab1e6c5bb0bdb6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.1_rm1/sunny_Building_2b_step35_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:1118d385e00f89199bfa15fd4a05d2585b49ee3c84a34000045d27417dd720e7 -size 1818642 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/config.yaml b/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/config.yaml deleted file mode 100644 index e43441ed9e20b079dbbcc497a7aae4effba85c8b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/console.log b/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/console.log deleted file mode 100644 index 8fcceeca4135b9223b1bab1551c33158c2467123..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 14:57:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:57:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:57:42|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:57:42|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:57:43|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:57:43|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:57:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:57:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/config.yaml -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_bg0.5_rm1'] -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_bg0.5_rm1 -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.json -[06-21 14:57:49|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 15:08:20|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1_control_edge.mp4 -[06-21 15:08:20|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:08:22|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/debug.log b/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/debug.log deleted file mode 100644 index 65165f43e95ff39469f622bde07d75392faa0dfe..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 14:57:14|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 14:57:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:57:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:57:33|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:57:34|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:57:34|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 14:57:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 14:57:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 14:57:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 14:57:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 14:57:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 14:57:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 14:57:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 14:57:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 14:57:35|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 14:57:35|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 14:57:35|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 14:57:35|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 14:57:35|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 14:57:36|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:57:36|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 14:57:36|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:57:36|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 14:57:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:57:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:57:38|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 14:57:38|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.93 s -[06-21 14:57:41|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:57:41|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:41|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.12 s -[06-21 14:57:42|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.89 s -[06-21 14:57:42|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.32 s -[06-21 14:57:42|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.32 s -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 14:57:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 14:57:42|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 14:57:42|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:57:42|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:57:43|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 14:57:43|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 14:57:43|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 14:57:43|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 14:57:43|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:57:43|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:57:47|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 14:57:47|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 14:57:47|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:57:47|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 11.24 s -[06-21 14:57:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:57:47|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:57:47|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:57:48|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.22.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:48|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:57:49|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 14:57:49|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 14:57:49|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/config.yaml -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_bg0.5_rm1'] -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_bg0.5_rm1 -[06-21 14:57:49|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_Building_2b_step35_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.json -[06-21 14:57:49|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:57:49|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4 -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 14:57:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 14:57:50|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:57:50|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:57:50|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:57:50|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:57:50|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:58:08|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:03:14|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 15:03:14|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 15:03:14|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 15:03:14|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 15:03:14|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:03:14|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 15:03:14|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:03:16|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:08:19|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.81643717642874 -[06-21 15:08:19|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:08:20|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1_control_edge.mp4 -[06-21 15:08:20|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:08:20|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:08:22|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/spec.json b/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/spec.json deleted file mode 100644 index 3246a162d3dbaaa0ff3cf0e60220a9dc8732ab42..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_Building_2b_step35_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.json b/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.json deleted file mode 100644 index c416304989cacb20ca3aadd1ae46f546679a2e08..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_Building_2b_step35_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.mp4 deleted file mode 100644 index 0c22a8e3cd2c507874e1556e956665462c564872..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:10ad35b935a688a71fa54a56dab6e202993e0d713ebcd03680a7cc2dd6efd3d5 -size 7012659 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.txt b/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.txt deleted file mode 100644 index 20a963b13c72a11374e0cef9d7e75383860a19e6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index a7e58d7f057ee0f0db3dd0132c780ecd3d41a7e8..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_bg0.5_rm1/sunny_Building_2b_step35_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:7a99f3639d51bc435cf50318e1c689dd0c653511fe4a724911e93c08403523ea -size 1859428 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml deleted file mode 100644 index afe8ff35817b36a568d1a97dd29b183400081b5f..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/console.log b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/console.log deleted file mode 100644 index e0ce09d00b88338de0d4fb9e71595af8de3ce3d5..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 15:09:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:09:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:09:11|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:09:11|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:09:12|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:09:12|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:09:16|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 15:09:16|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_masked_bg0.1_rm0.5'] -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_masked_bg0.1_rm0.5 -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.json -[06-21 15:09:18|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 15:19:49|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 -[06-21 15:19:49|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:19:50|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/debug.log b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/debug.log deleted file mode 100644 index df40d9179d06285c78432212304f247562e814e7..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 15:08:36|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 15:08:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:08:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:09:01|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:09:02|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:09:03|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 15:09:03|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 15:09:03|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 15:09:03|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 15:09:03|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 15:09:03|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 15:09:03|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 15:09:03|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 15:09:03|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 15:09:03|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 15:09:03|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 15:09:03|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 15:09:03|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 15:09:03|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:09:03|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 15:09:04|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 15:09:04|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 15:09:04|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 15:09:04|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:09:04|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 15:09:04|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:09:04|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 15:09:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:09:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:09:06|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 15:09:06|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 2.13 s -[06-21 15:09:10|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:09:10|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:10|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.10 s -[06-21 15:09:11|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.93 s -[06-21 15:09:11|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.26 s -[06-21 15:09:11|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.26 s -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 15:09:11|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 15:09:11|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 15:09:11|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:09:11|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:09:12|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 15:09:12|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 15:09:12|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 15:09:12|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 15:09:12|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:09:12|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:09:16|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 15:09:16|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 15:09:16|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:09:16|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 11.66 s -[06-21 15:09:16|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 15:09:16|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:09:16|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:09:17|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:09:17|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 15:09:17|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 15:09:17|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/config.yaml -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_masked_bg0.1_rm0.5'] -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_masked_bg0.1_rm0.5 -[06-21 15:09:18|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_Building_2b_step35_masked_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.json -[06-21 15:09:18|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:09:18|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4 -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 179 -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4 -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 15:09:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 15:09:19|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 15:09:19|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 15:09:19|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:09:19|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 15:09:19|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:09:37|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:14:43|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 15:14:43|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 15:14:43|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 15:14:43|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 15:14:43|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:14:43|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 15:14:43|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:14:46|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:19:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.7356735684443 -[06-21 15:19:48|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:19:49|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 -[06-21 15:19:49|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:19:49|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:19:50|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/spec.json b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/spec.json deleted file mode 100644 index b094c4d3388f2b98218a35777c6066a06ff32858..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "sunny_Building_2b_step35_masked_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.json b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.json deleted file mode 100644 index b719f5b738566e04893f15e7821e7d87ae1fc1f7..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_Building_2b_step35_masked_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.mp4 deleted file mode 100644 index 28e192a9d59c4d10603a1e4de8cc314dfea0ca09..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:c86a53bca586cdf077e991f725099c3720ba69a721afca7bab8623349989b0a1 -size 2158465 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.txt b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.txt deleted file mode 100644 index 20a963b13c72a11374e0cef9d7e75383860a19e6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 5d61c5511c39e785ea87e38ff1d8ab1e19c5c34b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm0.5/sunny_Building_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:adfe5546296b1b0c9781030eedb4c4093c741c3728ed0d113a9f65475b075cb3 -size 244721 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/config.yaml b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/config.yaml deleted file mode 100644 index ec2c480f89870bf1705b8d541fef0b03391cceef..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/console.log b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/console.log deleted file mode 100644 index b86d39aeca5ccda4538d02da02db5961b4fb255b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 15:20:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:20:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:20:12|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:20:12|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:20:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:20:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:20:17|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 15:20:17|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/config.yaml -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_masked_bg0.1_rm1'] -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_masked_bg0.1_rm1 -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.json -[06-21 15:20:18|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 15:30:49|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 -[06-21 15:30:49|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:30:51|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/debug.log b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/debug.log deleted file mode 100644 index 3b5c8f4c80d4fc4549e4f8fa4e19e3c486dfa060..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 15:19:53|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 15:19:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:19:54|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:20:05|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:20:05|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:20:06|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 15:20:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 15:20:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 15:20:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 15:20:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 15:20:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 15:20:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 15:20:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 15:20:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 15:20:06|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 15:20:06|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 15:20:06|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 15:20:06|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 15:20:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 15:20:06|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:20:07|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 15:20:07|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:20:07|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 15:20:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:20:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:20:08|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 15:20:08|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.03 s -[06-21 15:20:11|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:20:11|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:11|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.07 s -[06-21 15:20:12|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 15:20:12|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.11 s -[06-21 15:20:12|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.11 s -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 15:20:12|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 15:20:12|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 15:20:12|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:20:12|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:20:13|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 15:20:13|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 15:20:13|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 15:20:13|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 15:20:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:20:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:20:16|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 15:20:16|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 15:20:16|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:20:17|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 9.88 s -[06-21 15:20:17|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 15:20:17|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:20:17|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:20:18|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:20:18|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 15:20:18|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 15:20:18|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 15:20:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/config.yaml -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_masked_bg0.1_rm1'] -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_masked_bg0.1_rm1 -[06-21 15:20:18|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_Building_2b_step35_masked_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.json -[06-21 15:20:18|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:20:18|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 15:20:18|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 15:20:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 15:20:18|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4 -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4 -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 15:20:19|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:20:19|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 15:20:19|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:20:37|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:25:44|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 15:25:44|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 15:25:44|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 15:25:44|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 15:25:44|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:25:44|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 15:25:44|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:25:47|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:30:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.81072038947605 -[06-21 15:30:49|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:30:49|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 -[06-21 15:30:49|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:30:50|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:30:51|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/spec.json b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/spec.json deleted file mode 100644 index 4868a2a3b093704347bc2ce5e38ba9943d1073bc..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "sunny_Building_2b_step35_masked_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.json b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.json deleted file mode 100644 index 0f101444946b646297dcbc621f2dbe3815a028b1..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_Building_2b_step35_masked_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.mp4 deleted file mode 100644 index d8e146e9f125fbe745ca2845a62ea56e44958c00..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:639cc9e3fdb8521314f90ee66a919e062339b5f4d81ad88a85eafe97225b3676 -size 1979334 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.txt b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.txt deleted file mode 100644 index 20a963b13c72a11374e0cef9d7e75383860a19e6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index ad156f681a583cd208c5e2ce37c20122790deffc..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.1_rm1/sunny_Building_2b_step35_masked_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:5c20e131e064f9a771e23ca487faedf896891a1143f6a48be5f348e6b51ac994 -size 291491 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/config.yaml b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/config.yaml deleted file mode 100644 index 30803b8eea92d4862bfd694036a7918d7ebb69b0..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/console.log b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/console.log deleted file mode 100644 index 2af82e0415fdd50c1435b33fbb31765f24ce4386..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 15:31:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:31:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:31:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:31:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:31:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:31:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:31:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 15:31:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/config.yaml -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_masked_bg0.5_rm1'] -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_masked_bg0.5_rm1 -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.json -[06-21 15:31:24|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 15:41:58|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 -[06-21 15:41:58|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:41:59|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/debug.log b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/debug.log deleted file mode 100644 index 5a4ff70031376518583657c8fc771c8a0d82e912..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 15:30:54|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 15:30:55|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:30:55|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 15:31:06|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:31:06|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 15:31:07|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 15:31:07|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 15:31:07|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 15:31:07|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 15:31:07|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 15:31:07|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 15:31:07|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 15:31:07|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 15:31:07|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 15:31:07|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 15:31:07|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 15:31:07|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 15:31:07|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 15:31:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 15:31:07|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:31:08|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 15:31:08|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 15:31:08|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 15:31:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 15:31:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 15:31:09|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 15:31:09|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.17 s -[06-21 15:31:12|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:31:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 15:31:13|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 15:31:13|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.12 s -[06-21 15:31:13|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.12 s -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 15:31:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 15:31:13|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 15:31:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 15:31:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:31:14|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 15:31:14|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 15:31:14|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 15:31:14|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 15:31:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 15:31:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 15:31:20|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 15:31:20|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 15:31:20|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 15:31:20|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 12.70 s -[06-21 15:31:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 15:31:20|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:31:21|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 15:31:23|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.24.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:23|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 15:31:24|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 15:31:24|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 15:31:24|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/config.yaml -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_2b_step35_masked_bg0.5_rm1'] -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_2b_step35_masked_bg0.5_rm1 -[06-21 15:31:24|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_Building_2b_step35_masked_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.json -[06-21 15:31:24|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 15:31:24|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4', 'edge_mask_prompt': None} -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4 -[06-21 15:31:24|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:31:25|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4 -[06-21 15:31:25|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 15:31:25|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 15:31:25|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 15:31:25|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 15:31:25|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 15:31:25|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:31:25|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 15:31:25|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:31:43|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:36:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 15:36:49|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 15:36:50|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 15:36:50|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 15:36:50|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:36:50|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 15:36:50|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:36:52|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 15:41:56|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 314.6420054823393 -[06-21 15:41:56|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:41:58|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 -[06-21 15:41:58|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 15:41:58|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 15:41:59|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/spec.json b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/spec.json deleted file mode 100644 index 22771d8daa5be4d2009cc6562212fbaeab30ffbe..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "sunny_Building_2b_step35_masked_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.json b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.json deleted file mode 100644 index 0a8baafc0bacfefa96a1468c6f0f4a8e5d789de4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_Building_2b_step35_masked_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/Building_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.mp4 deleted file mode 100644 index bf5d5d3a92fce5521f1ce6f3edfcf4244d3bd511..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:0e774da8d22737e5a781c1accd62363739e820e71b218e320438b8319bede426 -size 2047795 diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.txt b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.txt deleted file mode 100644 index 20a963b13c72a11374e0cef9d7e75383860a19e6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index 47475c3689a750b185cac16f33177181588b21a2..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/2b_step35_masked_bg0.5_rm1/sunny_Building_2b_step35_masked_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:dfba067cb44ba645d6cbd3198eee3656c2a025a9aff66d181e310e972aba4469 -size 294166 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/config.yaml deleted file mode 100644 index ffae92a4056bc999b5f785d5fc309dfe63828c33..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/console.log b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/console.log deleted file mode 100644 index 987cbeaa35624ed35de4bd8783938eb12222e481..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 14:29:29|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 14:29:29|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 14:29:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:29:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:29:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:29:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:29:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:29:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:29:37|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 14:29:37|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/config.yaml -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_distilled_step4_bg0.1_rm0.5'] -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_distilled_step4_bg0.1_rm0.5 -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.json -[06-21 14:30:02|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:31:08|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 14:31:09|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 -[06-21 14:31:09|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:31:10|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/debug.log b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/debug.log deleted file mode 100644 index 9ad0c3084bb903c490cfd83b688dfe040f16385b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 14:29:15|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 14:29:16|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:29:16|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:29:27|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:29:27|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:29:27|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 14:29:28|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 14:29:28|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 14:29:28|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 14:29:28|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 14:29:28|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 14:29:28|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 14:29:28|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 14:29:28|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 14:29:28|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 14:29:28|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 14:29:28|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 14:29:28|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 14:29:28|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 14:29:28|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 14:29:29|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 14:29:29|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 14:29:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 14:29:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 14:29:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 14:29:29|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 14:29:30|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 14:29:30|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 14:29:30|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 14:29:30|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 14:29:30|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 14:29:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:29:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:29:30|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 14:29:30|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 14:29:31|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 14:29:31|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 14:29:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:29:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:29:34|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 14:29:34|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 14:29:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:29:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:29:35|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:35|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 14:29:36|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 14:29:36|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 14:29:36|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 6.48 s -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:29:36|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:36|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:29:37|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 14:29:37|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 14:29:37|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:29:37|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:29:37|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:29:37|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 14:29:37|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 14:29:37|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 14:29:37|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 14:29:37|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 7.81 s -[06-21 14:29:37|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 14:29:37|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 14:29:38|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 14:30:01|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 14:30:01|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:01|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:30:02|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 14:30:02|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 14:30:02|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.4._checkpoint_wrapped_module.cross_attn.q_proj.weight', 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['sunny_Building_distilled_step4_bg0.1_rm0.5'] -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_distilled_step4_bg0.1_rm0.5 -[06-21 14:30:02|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_Building_distilled_step4_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.json -[06-21 14:30:02|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:30:02|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4 -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 179 -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 14:30:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 14:30:40|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 14:30:40|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 14:31:08|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.72203822201118 -[06-21 14:31:08|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 14:31:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:31:09|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 -[06-21 14:31:09|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:31:09|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:31:10|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/spec.json b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/spec.json deleted file mode 100644 index d5303b70e7612586e7a47a09c86ab4eb977293ca..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_Building_distilled_step4_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.json b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.json deleted file mode 100644 index adeead285c61fb6a760398fef3ef03aa419c6b5c..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_Building_distilled_step4_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.mp4 b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.mp4 deleted file mode 100644 index ce98b5b5ea78001259335e6cd366865c848687b1..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:58c4e6df8a9d964ce04f895393ccc7fcefe2c1002237c2bcfccf88ce4c112f5f -size 2050044 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.txt b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.txt deleted file mode 100644 index 20a963b13c72a11374e0cef9d7e75383860a19e6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 31517dea0588b3196cdefd6c05d01c13532f321a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm0.5/sunny_Building_distilled_step4_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:82d37f9770a7b373f8f9fb16267abb84131023d9ecda8dcc622bb8cf91dbfb93 -size 1419864 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/config.yaml b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/config.yaml deleted file mode 100644 index a18ed23158658c01dfa6e070c5127e2d676911d0..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/console.log b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/console.log deleted file mode 100644 index 041654ea7f33755bd00f67d2e94c739b955cf9ba..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 14:31:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 14:31:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 14:31:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:31:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:31:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:31:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:31:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:31:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:31:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 14:31:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/config.yaml -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_distilled_step4_bg0.1_rm1'] -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_distilled_step4_bg0.1_rm1 -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.json -[06-21 14:31:36|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:32:42|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 14:32:43|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 -[06-21 14:32:43|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:32:45|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/debug.log b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/debug.log deleted file mode 100644 index d7ace301a0d3a9271f35e5c25b18b102187c1555..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 14:31:13|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 14:31:14|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:31:14|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:31:25|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:31:25|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:31:26|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 14:31:26|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 14:31:26|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 14:31:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 14:31:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 14:31:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 14:31:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 14:31:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 14:31:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 14:31:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 14:31:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 14:31:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 14:31:26|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 14:31:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 14:31:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 14:31:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 14:31:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 14:31:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 14:31:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 14:31:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 14:31:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 14:31:27|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 14:31:27|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 14:31:27|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 14:31:27|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 14:31:27|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 14:31:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:31:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:31:28|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 14:31:28|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 14:31:28|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 14:31:28|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 14:31:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:31:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:31:32|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 14:31:32|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 14:31:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:31:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.66 s -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 14:31:33|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 14:31:33|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 14:31:33|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 6.47 s -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:31:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:31:34|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:31:34|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 14:31:34|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 14:31:34|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:31:35|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:31:35|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:31:35|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 14:31:35|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 14:31:35|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 14:31:35|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 14:31:35|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 7.81 s -[06-21 14:31:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 14:31:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 14:31:35|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 14:31:36|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 14:31:36|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:31:36|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 14:31:36|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 14:31:36|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.4._checkpoint_wrapped_module.cross_attn.q_proj.weight', 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['sunny_Building_distilled_step4_bg0.1_rm1'] -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_distilled_step4_bg0.1_rm1 -[06-21 14:31:36|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_Building_distilled_step4_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.json -[06-21 14:31:36|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:31:36|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:31:36|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 14:31:36|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 14:31:36|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:31:36|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 14:31:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 14:31:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 14:31:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 14:31:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4 -[06-21 14:31:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:31:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 14:31:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 14:32:14|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 14:32:14|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 14:32:42|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.725967489997856 -[06-21 14:32:42|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 14:32:42|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:32:43|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 -[06-21 14:32:43|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:32:43|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:32:45|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/spec.json b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/spec.json deleted file mode 100644 index afc13100837707d6f127de8061330246cbc76700..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_Building_distilled_step4_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.json b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.json deleted file mode 100644 index 5d6b3d33bf88e6ce53922b95dc7ef3a6dbe92c12..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_Building_distilled_step4_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.mp4 b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.mp4 deleted file mode 100644 index 907fe0f6de85806067d71ad849917359be36e384..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:248422038ae7df179415aa61f807aaa791f7678ec5f975fcd7e2e58772c19dd7 -size 3619125 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.txt b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.txt deleted file mode 100644 index 20a963b13c72a11374e0cef9d7e75383860a19e6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 4e05a50fa2ad1e0a28d85922afab1e6c5bb0bdb6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.1_rm1/sunny_Building_distilled_step4_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:1118d385e00f89199bfa15fd4a05d2585b49ee3c84a34000045d27417dd720e7 -size 1818642 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/config.yaml b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/config.yaml deleted file mode 100644 index d524a4c81e93d2b5fa8e45729510a671dfac0ad4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/console.log b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/console.log deleted file mode 100644 index 0a894c33b1d2721bcee88975bd0c9dd241cf2ad4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 14:33:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 14:33:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 14:33:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:33:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:33:02|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:33:02|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:33:06|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:33:06|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:33:09|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 14:33:09|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/config.yaml -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_Building_distilled_step4_bg0.5_rm1'] -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_distilled_step4_bg0.5_rm1 -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.json -[06-21 14:33:10|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:34:16|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 14:34:17|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 -[06-21 14:34:18|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:34:19|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/debug.log b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/debug.log deleted file mode 100644 index 6559108102ba77679afbb5b0fc377fb96bc6c835..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 14:32:48|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 14:32:49|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:32:49|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:32:59|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:33:00|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:33:00|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 14:33:00|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 14:33:00|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 14:33:00|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 14:33:00|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 14:33:00|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 14:33:00|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 14:33:00|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 14:33:00|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 14:33:00|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 14:33:00|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 14:33:00|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 14:33:00|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 14:33:00|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 14:33:00|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 14:33:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 14:33:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 14:33:01|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 14:33:01|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 14:33:01|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 14:33:01|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 14:33:01|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 14:33:01|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 14:33:01|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 14:33:01|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 14:33:01|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 14:33:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:33:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:33:02|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 14:33:02|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 14:33:02|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 14:33:02|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 14:33:02|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:33:02|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:33:06|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 14:33:06|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 14:33:06|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:33:06|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:33:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.66 s -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 14:33:08|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 14:33:08|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 14:33:08|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 6.47 s -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:33:08|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:08|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:33:09|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 14:33:09|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 14:33:09|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:33:09|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:33:09|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:33:09|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 14:33:09|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 14:33:09|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 14:33:09|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 14:33:09|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 7.81 s -[06-21 14:33:09|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 14:33:09|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 14:33:09|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 14:33:10|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 14:33:10|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:33:10|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 14:33:10|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 14:33:10|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.4._checkpoint_wrapped_module.cross_attn.q_proj.weight', 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['sunny_Building_distilled_step4_bg0.5_rm1'] -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_Building_distilled_step4_bg0.5_rm1 -[06-21 14:33:10|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_Building_distilled_step4_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.json -[06-21 14:33:10|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:33:10|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 14:33:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 14:33:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 14:33:11|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:33:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 14:33:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 14:33:11|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 14:33:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 14:33:11|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4 -[06-21 14:33:11|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:33:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 14:33:11|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 14:33:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 14:33:48|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 14:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.700228346860968 -[06-21 14:34:16|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 14:34:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:34:17|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 -[06-21 14:34:18|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:34:18|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:34:19|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/spec.json b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/spec.json deleted file mode 100644 index 57d6536a21efdae50a93cade8468d5c5a439cf38..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_Building_distilled_step4_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.json b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.json deleted file mode 100644 index 26365bbd67e8a23fbef1d6b7f942a4dfd650a9ee..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_Building_distilled_step4_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Modern glass towers, plain concrete blocks, melted or warped facades, floating disconnected structures.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.mp4 b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.mp4 deleted file mode 100644 index 9f17baa736c0ad4a955b7717aaed5cd839930338..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e802e2a36bd5f770d8dc69a353b10a7b28dba30af37e1ddc0d34ae386f619aea -size 3519220 diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.txt b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.txt deleted file mode 100644 index 20a963b13c72a11374e0cef9d7e75383860a19e6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera in bright daylight. The streets are lined with ornate classical stone buildings featuring columns, cornices and tall arched windows, their facades warmly lit by the sun. A road network with painted lane markings, stop lines and pedestrian crosswalks runs through the scene, multiple vehicles move through the junction, and the camera follows the moving ego vehicle smoothly. Photorealistic, soft shadows, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index a7e58d7f057ee0f0db3dd0132c780ecd3d41a7e8..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/Building/distilled_step4_bg0.5_rm1/sunny_Building_distilled_step4_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:7a99f3639d51bc435cf50318e1c689dd0c653511fe4a724911e93c08403523ea -size 1859428 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/config.yaml deleted file mode 100644 index 50bca43ae9736c93e7baf9d4091496d6ddff23b4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/console.log b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/console.log deleted file mode 100644 index 3f209a99834544bb201d3e9b0caf8cee86f08c81..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 13:18:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:18:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:22:49|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:22:49|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:22:50|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:22:50|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:22:54|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 13:22:54|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/config.yaml -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_bg0.1_rm0.5'] -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_bg0.1_rm0.5 -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.json -[06-21 13:23:02|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:33:39|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 -[06-21 13:33:39|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:33:40|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/debug.log b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/debug.log deleted file mode 100644 index 6191d68f6ace4c114e3b896dd7441e7f42a0bf60..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 13:18:21|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 13:18:22|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:18:22|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:18:32|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:18:33|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:18:33|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 13:18:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 13:18:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 13:18:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 13:18:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 13:18:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 13:18:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 13:18:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 13:18:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 13:18:33|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 13:18:34|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 13:18:34|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 13:18:34|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 13:18:34|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 13:18:35|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 13:18:35|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 13:18:35|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 13:18:35|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 13:18:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:18:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:18:36|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 13:18:36|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 0.98 s -[06-21 13:22:48|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:22:48|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:48|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 13:22:49|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 13:22:49|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 253.05 s -[06-21 13:22:49|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 253.05 s -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 13:22:49|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 13:22:49|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 13:22:49|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:22:49|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:22:50|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 13:22:50|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 13:22:50|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 13:22:50|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 13:22:50|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:22:50|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:22:54|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 13:22:54|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 13:22:54|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:22:54|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 259.11 s -[06-21 13:22:54|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 13:22:54|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:22:54|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:23:02|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:23:02|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 13:23:02|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 13:23:02|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/config.yaml -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_bg0.1_rm0.5'] -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_bg0.1_rm0.5 -[06-21 13:23:02|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_weather_2b_step35_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.json -[06-21 13:23:02|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:23:02|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4 -[06-21 13:23:02|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 179 -[06-21 13:23:03|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 13:23:03|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 13:23:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 13:23:03|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 13:23:03|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:23:03|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 13:23:03|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:23:21|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:28:32|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 13:28:32|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 13:28:33|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 13:28:33|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 13:28:33|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:28:33|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 13:28:33|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:28:35|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:33:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 316.47421493846923 -[06-21 13:33:38|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:33:39|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 -[06-21 13:33:39|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:33:39|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:33:40|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/spec.json b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/spec.json deleted file mode 100644 index c66df112b413fb22d80c3eb74d28202a30df84f2..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_weather_2b_step35_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.json b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.json deleted file mode 100644 index 8bc857a664ffda441f10eadd2d1b80e0141536ca..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_weather_2b_step35_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.mp4 deleted file mode 100644 index 528d8633750427ff3f0e066d30458d09529cda6e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:8b583e325e92bcd84cf2be19666ae49c8fa70f7ab1b01f98a5a49922a06958f6 -size 2088280 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.txt b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.txt deleted file mode 100644 index 464b6055f679cb63d0db8e54bd910217c87b403b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 31517dea0588b3196cdefd6c05d01c13532f321a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm0.5/sunny_weather_2b_step35_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:82d37f9770a7b373f8f9fb16267abb84131023d9ecda8dcc622bb8cf91dbfb93 -size 1419864 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/config.yaml b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/config.yaml deleted file mode 100644 index 58428e8c99a1e5441d433c76537e72f856d45e0d..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/console.log b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/console.log deleted file mode 100644 index f7a9db646c87ef48634aa7232d59513a39de8958..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 13:34:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:34:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:34:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:34:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:34:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:34:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:34:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 13:34:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/config.yaml -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_bg0.1_rm1'] -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_bg0.1_rm1 -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.json -[06-21 13:34:15|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:44:48|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1_control_edge.mp4 -[06-21 13:44:48|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:44:50|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/debug.log b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/debug.log deleted file mode 100644 index 93a49505c231e8c064e54330a3bf6492619f9f8b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 13:33:46|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 13:33:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:33:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:33:58|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:33:59|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:33:59|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 13:33:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 13:33:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 13:33:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 13:33:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 13:33:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 13:33:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 13:33:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 13:33:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 13:33:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 13:33:59|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 13:33:59|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 13:33:59|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 13:33:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 13:34:00|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 13:34:00|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 13:34:00|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 13:34:00|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 13:34:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:34:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:34:01|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 13:34:01|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.03 s -[06-21 13:34:04|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 13:34:04|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:04|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 13:34:05|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.85 s -[06-21 13:34:05|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.16 s -[06-21 13:34:05|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.16 s -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 13:34:05|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 13:34:05|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 13:34:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:34:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:34:07|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 13:34:07|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 13:34:07|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 13:34:07|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 13:34:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:34:07|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:34:13|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 13:34:13|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 13:34:13|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:34:13|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 13.62 s -[06-21 13:34:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 13:34:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:34:14|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:34:15|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:34:15|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 13:34:15|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 13:34:15|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 13:34:15|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/config.yaml -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_bg0.1_rm1'] -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_bg0.1_rm1 -[06-21 13:34:15|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_weather_2b_step35_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.json -[06-21 13:34:15|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:34:15|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:34:15|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 13:34:15|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4 -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 13:34:16|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:34:16|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 13:34:16|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:34:34|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:39:42|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 13:39:42|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 13:39:42|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 13:39:42|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 13:39:42|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:39:42|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 13:39:42|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:39:44|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:44:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 314.45178023993503 -[06-21 13:44:47|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:44:48|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1_control_edge.mp4 -[06-21 13:44:48|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:44:48|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:44:50|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/spec.json b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/spec.json deleted file mode 100644 index e9140e9a464e13629056ff305dc90c859a0fb66e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_weather_2b_step35_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.json b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.json deleted file mode 100644 index a9f53a2515379d289355a8634f46435b61ad2180..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_weather_2b_step35_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.mp4 deleted file mode 100644 index 440717c90e3afa53e1033a2de729fac457a6f7ff..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:af8effb5fc75f14916c234d67e97d6c01864dadf776e2c7f53ed7c8ff24c6ab5 -size 5738794 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.txt b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.txt deleted file mode 100644 index 464b6055f679cb63d0db8e54bd910217c87b403b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 4e05a50fa2ad1e0a28d85922afab1e6c5bb0bdb6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.1_rm1/sunny_weather_2b_step35_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:1118d385e00f89199bfa15fd4a05d2585b49ee3c84a34000045d27417dd720e7 -size 1818642 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/config.yaml b/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/config.yaml deleted file mode 100644 index d6b3f992d91976283d9b0bf3b0f6b2da9b0449d8..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/console.log b/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/console.log deleted file mode 100644 index a1db5958286a23a9a1561729e9259bd0371f555a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 13:45:18|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:45:18|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:45:24|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:45:24|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:45:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 13:45:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/config.yaml -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_bg0.5_rm1'] -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_bg0.5_rm1 -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.json -[06-21 13:45:29|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:56:00|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1_control_edge.mp4 -[06-21 13:56:00|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:56:01|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/debug.log b/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/debug.log deleted file mode 100644 index f7e46047d4d961411ccf10b32470c56b8b7d0efa..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/debug.log +++ /dev/null @@ -1,973 +0,0 @@ -[06-21 13:44:55|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 13:44:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:44:57|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:45:15|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:45:16|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:45:17|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 13:45:17|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 13:45:17|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 13:45:17|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 13:45:17|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 13:45:17|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 13:45:17|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 13:45:17|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 13:45:17|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 13:45:17|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 13:45:17|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 13:45:17|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 13:45:17|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 13:45:17|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 13:45:17|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 13:45:18|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 13:45:18|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 13:45:18|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 13:45:18|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:45:18|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:45:19|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 13:45:19|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.04 s -[06-21 13:45:22|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:45:22|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:22|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 13:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.83 s -[06-21 13:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.11 s -[06-21 13:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.11 s -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 13:45:23|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 13:45:23|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 13:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:45:23|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:45:24|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 13:45:24|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 13:45:24|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 13:45:24|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 13:45:24|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:45:24|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:45:28|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 13:45:28|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 13:45:28|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:45:28|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.01 s -[06-21 13:45:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 13:45:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:45:28|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:45:29|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.22.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:45:29|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 13:45:29|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 13:45:29|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 13:45:29|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/config.yaml -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_bg0.5_rm1'] -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_bg0.5_rm1 -[06-21 13:45:29|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_weather_2b_step35_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.json -[06-21 13:45:29|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:45:29|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:45:29|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 13:45:29|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4 -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 13:45:30|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:45:30|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 13:45:30|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:45:48|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:50:55|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 13:50:55|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 13:50:55|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 13:50:55|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 13:50:55|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:50:55|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 13:50:55|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:50:57|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:55:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.2856137724593 -[06-21 13:55:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:56:00|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1_control_edge.mp4 -[06-21 13:56:00|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:56:00|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:56:01|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/spec.json b/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/spec.json deleted file mode 100644 index 1b5e33ce65d0d0aaa1f228309578507c50e5c4f4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_weather_2b_step35_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.json b/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.json deleted file mode 100644 index e68a523520e08bf9a17cf1947ee0aa21a43a9075..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_weather_2b_step35_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.mp4 deleted file mode 100644 index aca6d5904317ba2a1251ebce258b7992d289c775..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:ce93583e17661d0d91f5af79f9065dba81310f9b8bf660f12ca33f92240e47b5 -size 6483354 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.txt b/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.txt deleted file mode 100644 index 464b6055f679cb63d0db8e54bd910217c87b403b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index a7e58d7f057ee0f0db3dd0132c780ecd3d41a7e8..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_bg0.5_rm1/sunny_weather_2b_step35_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:7a99f3639d51bc435cf50318e1c689dd0c653511fe4a724911e93c08403523ea -size 1859428 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml deleted file mode 100644 index 3330d84b0005f56ed3b084414caf998f4f47f9e1..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/console.log b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/console.log deleted file mode 100644 index 4110bbd338d43559087449a746b9ac65a52f6703..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 13:56:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:56:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:56:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:56:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:56:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:56:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:56:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 13:56:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_masked_bg0.1_rm0.5'] -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_masked_bg0.1_rm0.5 -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.json -[06-21 13:56:37|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 14:07:07|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 -[06-21 14:07:07|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:07:09|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/debug.log b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/debug.log deleted file mode 100644 index e21081f35c2fb4d60ef4b81ad7057ea64a4f0b9d..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 13:56:12|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 13:56:12|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:56:12|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:56:23|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:56:24|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:56:24|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 13:56:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 13:56:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 13:56:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 13:56:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 13:56:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 13:56:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 13:56:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 13:56:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 13:56:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 13:56:24|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 13:56:24|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 13:56:24|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 13:56:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 13:56:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 13:56:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 13:56:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 13:56:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 13:56:25|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 13:56:25|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 13:56:25|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 13:56:25|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 13:56:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:56:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:56:26|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 13:56:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.12 s -[06-21 13:56:29|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 13:56:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 13:56:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.85 s -[06-21 13:56:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.15 s -[06-21 13:56:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.15 s -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 13:56:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 13:56:30|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 13:56:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:56:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:56:31|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 13:56:31|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 13:56:31|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 13:56:31|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 13:56:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:56:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:56:35|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 13:56:35|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 13:56:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:56:35|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.06 s -[06-21 13:56:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 13:56:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:56:35|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 13:56:36|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.4.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:56:37|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 13:56:37|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 13:56:37|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/config.yaml -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_masked_bg0.1_rm0.5'] -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_masked_bg0.1_rm0.5 -[06-21 13:56:37|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_weather_2b_step35_masked_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.json -[06-21 13:56:37|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:56:37|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4 -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 179 -[06-21 13:56:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4 -[06-21 13:56:38|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:56:38|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 13:56:38|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 13:56:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 13:56:38|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 13:56:38|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:56:38|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 13:56:38|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 13:56:56|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:02:03|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 14:02:03|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 14:02:03|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:02:03|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:02:03|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:02:03|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:02:03|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:02:05|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:07:06|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.22715163009707 -[06-21 14:07:06|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:07:07|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 -[06-21 14:07:07|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:07:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:07:09|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/spec.json b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/spec.json deleted file mode 100644 index f5c044abccbc763f8b18a201736acd4a74258835..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "sunny_weather_2b_step35_masked_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.json b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.json deleted file mode 100644 index 60ab6760a99bc0f7726b729fbec868697bc5d372..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_weather_2b_step35_masked_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.mp4 deleted file mode 100644 index 6e5b0cf2f898e7b42109dede8c4cdebec7cff513..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:0062d7b3bff682541a97cfd9db533fc4300a2fe3b4554aeece46ae9ec2a59b33 -size 2008475 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.txt b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.txt deleted file mode 100644 index 464b6055f679cb63d0db8e54bd910217c87b403b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 57d19047156e4e2e4999849fd2eccc6313ed927e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm0.5/sunny_weather_2b_step35_masked_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:10edda3086229ecb752df1c5297480d20bfadf17f3d8e650e75fec5138b09e85 -size 1665701 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/config.yaml b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/config.yaml deleted file mode 100644 index 92d6a5f6964c35fb49674697e64081a87c81fef9..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/console.log b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/console.log deleted file mode 100644 index d021991ec5eb1e0fe8baf1e1bfed160a158c71f6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 14:07:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:07:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:07:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:07:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:07:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:07:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:07:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:07:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/config.yaml -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_masked_bg0.1_rm1'] -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_masked_bg0.1_rm1 -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.json -[06-21 14:07:37|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 14:18:08|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 -[06-21 14:18:08|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:18:10|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/debug.log b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/debug.log deleted file mode 100644 index 6f251e803e9500e66988e54089d71cd5f59ad0e2..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 14:07:12|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 14:07:12|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:07:12|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:07:23|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:07:23|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:07:24|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 14:07:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 14:07:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 14:07:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 14:07:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 14:07:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 14:07:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 14:07:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 14:07:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 14:07:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 14:07:24|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 14:07:24|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 14:07:24|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 14:07:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 14:07:25|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:07:25|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 14:07:25|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:07:25|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 14:07:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:07:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:07:26|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 14:07:26|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.29 s -[06-21 14:07:29|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 14:07:29|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:29|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 14:07:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.84 s -[06-21 14:07:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.12 s -[06-21 14:07:30|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.12 s -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 14:07:30|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 14:07:30|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 14:07:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:07:30|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:07:31|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 14:07:31|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 14:07:31|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 14:07:31|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 14:07:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:07:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:07:35|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 14:07:35|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 14:07:35|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:07:35|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.19 s -[06-21 14:07:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:07:35|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:07:35|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:07:36|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:36|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:07:37|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 14:07:37|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 14:07:37|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/config.yaml -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_masked_bg0.1_rm1'] -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_masked_bg0.1_rm1 -[06-21 14:07:37|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_weather_2b_step35_masked_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.json -[06-21 14:07:37|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:07:37|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4 -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4 -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 14:07:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 14:07:38|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:07:38|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:07:38|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:07:38|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:07:38|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:07:56|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:13:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 14:13:02|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 14:13:02|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:13:02|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:13:02|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:13:02|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:13:02|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:13:05|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:18:07|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 313.7368939309381 -[06-21 14:18:07|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:18:08|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 -[06-21 14:18:08|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:18:08|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:18:10|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/spec.json b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/spec.json deleted file mode 100644 index 73452f661fd808387e1b38b04e79d95e45101f3e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "sunny_weather_2b_step35_masked_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.json b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.json deleted file mode 100644 index fed0d0ecac9b44ad2c26e75a69a840d1017e95a4..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_weather_2b_step35_masked_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.mp4 deleted file mode 100644 index 4943630f662d7962f42beb966cda400ce49edb99..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:ea886d91f4a53db897a2c2b5b6f845cb0d916de8275616150545b9740f5cf1c0 -size 5578183 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.txt b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.txt deleted file mode 100644 index 464b6055f679cb63d0db8e54bd910217c87b403b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 0f511598b9ebb3a5709114063144abdc8c446d7e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.1_rm1/sunny_weather_2b_step35_masked_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:ae7776b7552010f01fb2efeb2ad5b475a27fe85f3a0bc5210c1c415d4afed6cd -size 2090009 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/config.yaml b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/config.yaml deleted file mode 100644 index cac8060872808ddae0a1e7758795a419e06cb0ec..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,882 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '1000' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'False' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - dataloaders: - image_data: - ratio: '0' - video_data: - dataloader: - batch_size: '1' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - video_data_1: - dataloader: - batch_size: '6' - cache_augment_fn: functools.partial(, n=1.8) - cache_size: '32' - concat_size: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control_and_image_context - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - num_video_frames: '1' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' - use_cache: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' -defaults: -- _self_ -- data_train: mock -- data_val: mock -- optimizer: fusedadamw -- scheduler: lambdalinear -- model: ddp -- callbacks: basic -- net: null -- conditioner: video_prediction_control_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dummy -- experiment: null -job: - cluster: null - group: vid2vid_2B_control - name: vid2vid_2B_control_720p_t24_control_layer4_cr1pt1_embedding_rectified_flow_with_image_context_with_image_data - project: cosmos_transfer2 - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - conditional_frame_timestep: -1.0 - conditional_frames_probs: - 0: 0.4 - 1: 0.4 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - reference_image_context: - _target_: - dropout_rate: '0.5' - input_key: - - images - - video - - image_context - num_token: '256' - output_key: null - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - conditioning_strategy: frame_replace - copy_weight_strategy: first_n - denoise_replace_gt_frames: true - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - high_sigma_ratio: 0.05 - high_sigma_timesteps_max: 1000 - high_sigma_timesteps_min: 980 - hint_keys: edge - init_lora_weights: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - lora_alpha: 32 - lora_rank: 32 - lora_target_modules: q_proj,k_proj,v_proj,output_proj,mlp.layer1,mlp.layer2 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_image_context_dim: '1152' - extra_per_block_abs_pos_emb: 'False' - img_context_deep_proj: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - share_q_in_i2v_cross_attn: 'False' - spatial_compression_factor: '8' - timestep_scale: '0.001' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - precision: bfloat16 - resolution: '720' - shift: 5 - state_ch: 16 - state_t: 24 - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - temporal_window: '16' - train_time_distribution: logitnormal - train_time_weight: uniform - use_dora: false - use_dynamic_shift: false - use_high_sigma_strategy: false - use_kerras_sigma_at_inference: false - use_lora: false - use_reference_image: true - use_torch_compile: false -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 8 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - eps: 1e-08 - fused: 'True' - lr: '8.63e-05' - model: null - optim_type: adamw - weight_decay: '0.001' -scheduler: - _target_: - cycle_lengths: - - '100000' - f_max: - - '0.5' - f_min: - - '0.2' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '200' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '200' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'True' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - every_n: '5000' - fix_batch_fp: null - fps: '16' - guidance: - - '0' - - '3' - - '7' - is_ema: 'False' - is_sample: 'True' - is_x0: 'False' - n_sample_to_save: '128' - n_viz_sample: '3' - n_x0_level: '4' - num_sampling_step: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - frame_loss_log: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - grad_clip: - _target_: - clip_norm: '0.1' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '100' - hit_thres: '300' - save_s3: 'True' - save_s3_every_log_n: '10' - load_base_model: - _target_: - config: null - trainer: null - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '200' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '200' - max_iter: '100000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'True' - max_diff: '1.5' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/console.log b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/console.log deleted file mode 100644 index 69fa5fea1babd210255849d6ec07b828d208c2c5..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/console.log +++ /dev/null @@ -1,18 +0,0 @@ -[06-21 14:18:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:18:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:18:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:18:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:18:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:18:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:18:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:18:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/config.yaml -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_masked_bg0.5_rm1'] -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_masked_bg0.5_rm1 -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.json -[06-21 14:18:38|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 14:29:10|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 -[06-21 14:29:10|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:29:12|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/debug.log b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/debug.log deleted file mode 100644 index 8f16300027d7a5db252d3dc32fe73e279675e836..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/debug.log +++ /dev/null @@ -1,975 +0,0 @@ -[06-21 14:18:13|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=False) -[06-21 14:18:14|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:18:14|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 14:18:25|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:18:25|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 14:18:26|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1') model='edge' checkpoint_path='s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000' experiment='edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5' config_file='cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/config.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 14:18:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 14:18:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 14:18:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 14:18:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 14:18:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 14:18:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 14:18:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 14:18:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 14:18:26|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 14:18:26|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_large_scale -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.exp_small_overfit -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment.experiment_list -[06-21 14:18:26|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:206:import_modules_recursively] Skipping module _submit as it starts with an underscore -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.exp_large_scale -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.transfer2.configs.vid2vid_transfer.experiment_av.experiment_list -[06-21 14:18:26|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2.experiments -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.agibot.cosmos_agibot_posttrain_example -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.multiview.cosmos_multiview_example -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview -[06-21 14:18:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2.experiments.singleview.cosmos_singleview_example -[06-21 14:18:26|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:91:load_model_from_checkpoint] Overriding config checkpoint path with: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:18:26|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 14:18:26|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:111:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24or1_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_uniform_hqv3p1_20250714_64N_rectified_flow_refimdrop0pt5/checkpoints/iter_000032000 -[06-21 14:18:26|WARNING|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:132:__init__] DiffusionModel: precision torch.bfloat16 -[06-21 14:18:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 14:18:27|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 14:18:27|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 14:18:27|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_tokenizer: 1.16 s -[06-21 14:18:31|INFO|cosmos_transfer2/_src/transfer2/networks/siglip2.py:65:get_siglip2_model_processor] -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #14-reference_image_context: - SigLip2EmbImgContext - input key: ['images', 'video', 'image_context'] - Param count: 0 - Trainable: None - Dropout rate: 0.5 - Input key: ['images', 'video', 'image_context'] - Output key: ['img_context_emb'] -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:18:31|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up I2VCrossAttentionFull. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on meta to cuda and broadcast model states: 0.08 s -[06-21 14:18:32|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model: 0.83 s -[06-21 14:18:32|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Creating PyTorch model and ema if enabled: 4.11 s -[06-21 14:18:32|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on DiffusionModel: set_up_model: 4.11 s -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:569:freeze_base_model] -Freezing base model - -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:607:freeze_base_model] ✓ Unfroze img_context_proj -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 0 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 1 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 2 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 3 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 4 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 5 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 6 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 7 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 8 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 9 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 10 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 11 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 12 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 13 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 14 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 15 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 16 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 17 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 18 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 19 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 20 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 21 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 22 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 23 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 24 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 25 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 26 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:622:freeze_base_model] ✓ Unfroze reference image weights in ControlAwareDiTBlock 27 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 0 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 1 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 2 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:637:freeze_base_model] ✓ Unfroze reference image weights in ControlEncoderDiTBlock 3 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:779:load_base_model] Done loading the base model checkpoint. -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 0-th block weight to control net's 0-th block -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 1-th block weight to control net's 1-th block -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 2-th block weight to control net's 2-th block -[06-21 14:18:32|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:532:copy_weights_to_control_branch] ======Copying base model's 3-th block weight to control net's 3-th block -[06-21 14:18:32|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 14:18:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 14:18:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:18:32|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 14:18:32|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 14:18:32|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 14:18:33|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 14:18:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 14:18:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 14:18:36|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 14:18:36|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 14:18:36|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:76:__init__] MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (img_context_proj): Sequential( - (0): Linear(in_features=1152, out_features=2048, bias=True) - (1): GELU(approximate='none') - ) - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): I2VCrossAttentionFull( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): DotProductAttention( - (flash_attention): FlashAttention() - (fused_attention): FusedAttention() - (unfused_attention): UnfusedDotProductAttention( - (scale_mask_softmax): FusedScaleMaskSoftmax() - (attention_dropout): Dropout(p=0, inplace=False) - ) - ) - (k_img): Linear(in_features=2048, out_features=2048, bias=False) - (v_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img): Linear(in_features=2048, out_features=2048, bias=False) - (q_img_norm): RMSNorm() - (k_img_norm): RMSNorm() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 14:18:36|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 10.05 s -[06-21 14:18:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/general/edge(61f5694b-0ad5-4ecd-8ad7-c8545627d125) -[06-21 14:18:36|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision b67b64abda3801a9aceddbff2bdb86126c06db74 general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:18:37|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:227:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt -[06-21 14:18:38|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:919:load_state_dict] load model in non-strict mode -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.24.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.24.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.attn_op._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_img_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 14:18:38|CRITICAL|cosmos_transfer2/_src/predict2/models/text2world_model_rectified_flow.py:920:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 14:18:38|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:271:load_model_state_dict_from_checkpoint] Checkpoint weights loaded from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/b67b64abda3801a9aceddbff2bdb86126c06db74/general/edge/61f5694b-0ad5-4ecd-8ad7-c8545627d125_ema_bf16.pt: None -[06-21 14:18:38|INFO|cosmos_transfer2/_src/predict2/utils/model_loader.py:273:load_model_state_dict_from_checkpoint] Checkpoint weights loaded successfully (strict=True). -[06-21 14:18:38|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:1015:compile_tokenizer_if_enabled] Tokenizer compilation disabled -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/config.yaml -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_2b_step35_masked_bg0.5_rm1'] -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_2b_step35_masked_bg0.5_rm1 -[06-21 14:18:38|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_weather_2b_step35_masked_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=35 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4'), mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.json -[06-21 14:18:38|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 14:18:38|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4', 'edge_mask_prompt': None} -[06-21 14:18:38|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 14:18:38|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 14:18:38|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:18:38|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:501:generate_img2world] Computing negative prompt text embeddings... -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4 -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4 -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 0 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:18:39|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:18:39|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:18:39|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:18:57|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:24:04|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 14:24:04|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 14:24:04|INFO|cosmos_transfer2/_src/transfer2/models/vid2vid_model_control_vace_rectified_flow.py:239:get_velocity_fn_from_batch] num_conditional_frames: 1 is set by data_batch[NUM_CONDITIONAL_FRAMES_KEY] -[06-21 14:24:05|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:255:get_condition_with_negative_prompt] Getting condition with image context -[06-21 14:24:05|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:24:05|INFO|cosmos_transfer2/_src/transfer2/configs/vid2vid_transfer/defaults/conditioner.py:257:get_condition_with_negative_prompt] Getting uncondition with negative prompt without image context -[06-21 14:24:05|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:24:07|WARNING|cosmos_transfer2/_src/transfer2/networks/siglip2_image_context.py:83:forward] No image_context provided, using zero latents -[06-21 14:29:09|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 314.1466989730252 -[06-21 14:29:10|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:29:10|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 -[06-21 14:29:10|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 14:29:10|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 14:29:12|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/spec.json b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/spec.json deleted file mode 100644 index cc1062f9e0564c07d97cb13c61903ccd31d3490e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/spec.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "name": "sunny_weather_2b_step35_masked_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 35, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4", - "control_weight": 1.0, - "mask_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4" - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.json b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.json deleted file mode 100644 index 689e5b637452c345ffa6914909e5b094c16046fe..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_weather_2b_step35_masked_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":35,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_masks/sunny/weather_mask.mp4","mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.mp4 deleted file mode 100644 index 14746a1860b4effeb3eba007815d17f634f3a961..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:30cb439d8b8688ad8f4600cba71376d0088a295826a419140af6fbc626fea9fd -size 6555571 diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.txt b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.txt deleted file mode 100644 index 464b6055f679cb63d0db8e54bd910217c87b403b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index 3691db77a46183e1e2ff4e8fbf0800ceb256f5cb..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/2b_step35_masked_bg0.5_rm1/sunny_weather_2b_step35_masked_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:363678c60e85c2017c742e268aff3ce36025bad0c3799e15dadd48810a21b9c6 -size 2156618 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/config.yaml b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/config.yaml deleted file mode 100644 index 9f1de798d7db4b3ce482379e44add32cdbe3739e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/console.log b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/console.log deleted file mode 100644 index c4da4b3fa5de85d7daf6db7d194dd8ece3776cd0..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 13:11:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 13:11:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 13:11:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:11:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:11:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:11:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:12:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:12:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:12:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 13:12:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/config.yaml -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_distilled_step4_bg0.1_rm0.5'] -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_distilled_step4_bg0.1_rm0.5 -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.json -[06-21 13:12:37|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:14:27|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 13:14:30|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 -[06-21 13:14:30|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:14:31|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/debug.log b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/debug.log deleted file mode 100644 index 0e84b423f3fab750a9c4cfe92dad76a38a3483d8..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 13:07:40|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 13:08:05|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:08:05|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:10:48|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:10:57|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:11:07|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 13:11:08|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 13:11:10|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 13:11:14|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 13:11:14|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 13:11:14|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 13:11:14|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 13:11:14|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 13:11:14|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 13:11:14|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 13:11:14|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 13:11:14|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 13:11:14|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 13:11:14|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 13:11:14|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 13:11:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 13:11:14|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 13:11:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 13:11:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 13:11:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 13:11:26|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 13:11:27|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 13:11:28|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 13:11:28|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 13:11:28|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 13:11:28|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 13:11:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:11:28|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:11:29|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 13:11:29|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 13:11:30|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 13:11:32|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 13:11:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:11:32|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:12:02|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 13:12:02|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 13:12:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:12:03|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:12:05|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:12:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 6.16 s -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 13:12:12|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 13:12:12|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 13:12:12|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 44.08 s -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:12:12|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:12|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:12:13|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 13:12:13|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 13:12:13|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:12:13|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:12:13|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:12:13|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 13:12:13|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 13:12:13|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 13:12:13|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 13:12:13|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 45.74 s -[06-21 13:12:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 13:12:13|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 13:12:14|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 13:12:37|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 13:12:37|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced 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13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.22.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.23.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key 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blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:12:37|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 13:12:37|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 13:12:37|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.4._checkpoint_wrapped_module.cross_attn.q_proj.weight', 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['sunny_weather_distilled_step4_bg0.1_rm0.5'] -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_distilled_step4_bg0.1_rm0.5 -[06-21 13:12:37|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_weather_distilled_step4_bg0.1_rm0.5' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.json -[06-21 13:12:37|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:12:37|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:12:37|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 13:12:37|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 13:12:41|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:12:42|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 13:12:55|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 13:12:55|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 13:12:55|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 13:12:55|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4 -[06-21 13:12:56|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 179 -[06-21 13:12:56|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 13:12:56|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 13:13:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 13:13:58|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 13:14:27|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 44.306865896098316 -[06-21 13:14:27|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 13:14:27|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:14:30|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 -[06-21 13:14:30|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:14:30|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:14:31|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.mp4 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/spec.json b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/spec.json deleted file mode 100644 index fcb3354ebe8c860d0d9a33fc969cb9d0d6e7e9ca..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_weather_distilled_step4_bg0.1_rm0.5", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.json b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.json deleted file mode 100644 index 009f3e49e02ad30c2a82ce0cd94cc1ea3d073a3c..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_weather_distilled_step4_bg0.1_rm0.5","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm0.5.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.mp4 b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.mp4 deleted file mode 100644 index 5183123e1273fa03bbf3ba82441054c8bdbb5ada..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:3eb54f18ecd51bef493939db03e879b2b03d38e5bd7882169c360a9644162d9d -size 1751565 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.txt b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.txt deleted file mode 100644 index 464b6055f679cb63d0db8e54bd910217c87b403b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 deleted file mode 100644 index 31517dea0588b3196cdefd6c05d01c13532f321a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm0.5/sunny_weather_distilled_step4_bg0.1_rm0.5_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:82d37f9770a7b373f8f9fb16267abb84131023d9ecda8dcc622bb8cf91dbfb93 -size 1419864 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/config.yaml b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/config.yaml deleted file mode 100644 index bd5ff997f00f2673a5c420d8e6785a86a6cbb717..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/console.log b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/console.log deleted file mode 100644 index d1cf31c0b63b9c2d50b1084ca43b63b58634fb0f..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 13:15:24|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 13:15:24|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 13:15:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:15:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:15:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:15:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:15:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:15:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:15:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 13:15:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/config.yaml -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_distilled_step4_bg0.1_rm1'] -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_distilled_step4_bg0.1_rm1 -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.json -[06-21 13:15:35|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:16:41|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 13:16:42|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 -[06-21 13:16:42|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:16:44|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/debug.log b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/debug.log deleted file mode 100644 index edbac2ea7403fb064d7405981e0ad7d816f7460b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 13:15:12|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 13:15:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:15:13|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:15:23|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:15:24|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:15:24|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 13:15:24|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 13:15:24|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 13:15:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 13:15:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 13:15:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 13:15:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 13:15:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 13:15:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 13:15:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 13:15:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 13:15:24|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 13:15:24|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 13:15:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 13:15:24|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 13:15:24|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 13:15:24|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 13:15:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 13:15:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 13:15:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 13:15:25|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 13:15:25|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 13:15:25|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 13:15:25|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 13:15:25|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 13:15:25|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 13:15:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:15:25|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:15:26|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 13:15:26|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 13:15:26|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 13:15:26|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 13:15:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:15:26|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:15:30|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 13:15:30|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 13:15:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:15:31|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:15:31|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:31|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 13:15:32|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 13:15:32|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 13:15:32|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 6.86 s -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:15:32|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:32|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:15:33|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.64 s -[06-21 13:15:33|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 13:15:33|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:15:33|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:15:33|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:15:33|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 13:15:33|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 13:15:33|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 13:15:33|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 13:15:33|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 8.19 s -[06-21 13:15:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 13:15:33|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 13:15:34|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 13:15:35|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 13:15:35|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:15:35|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 13:15:35|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 13:15:35|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.4._checkpoint_wrapped_module.cross_attn.q_proj.weight', 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['sunny_weather_distilled_step4_bg0.1_rm1'] -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_distilled_step4_bg0.1_rm1 -[06-21 13:15:35|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_weather_distilled_step4_bg0.1_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.json -[06-21 13:15:35|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:15:35|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:15:35|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 13:15:35|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 13:15:35|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:15:35|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 13:15:35|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 13:15:35|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 13:15:35|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 13:15:35|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4 -[06-21 13:15:36|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:15:36|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 13:15:36|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 13:16:13|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 13:16:13|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 13:16:41|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.672332453075796 -[06-21 13:16:41|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 13:16:41|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:16:42|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 -[06-21 13:16:42|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:16:42|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:16:44|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/spec.json b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/spec.json deleted file mode 100644 index 73000f8e5da4316c605eeca459c235b223fc8718..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_weather_distilled_step4_bg0.1_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.json b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.json deleted file mode 100644 index b934e2a066d7e03a4e5851cdcb08008d1b39305e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_weather_distilled_step4_bg0.1_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.1_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.mp4 b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.mp4 deleted file mode 100644 index 0089365f49955f136695beaf6d74c125a8c87664..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:50564370226ad6514e8df10ef9d31ce87349e01952ea164e18866feb0de43334 -size 3436600 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.txt b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.txt deleted file mode 100644 index 464b6055f679cb63d0db8e54bd910217c87b403b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 deleted file mode 100644 index 4e05a50fa2ad1e0a28d85922afab1e6c5bb0bdb6..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.1_rm1/sunny_weather_distilled_step4_bg0.1_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:1118d385e00f89199bfa15fd4a05d2585b49ee3c84a34000045d27417dd720e7 -size 1818642 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/config.yaml b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/config.yaml deleted file mode 100644 index e7811b0cfd3d4c1f4c97d71e26bca4ddda9a392e..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/config.yaml +++ /dev/null @@ -1,956 +0,0 @@ -checkpoint: - broadcast_via_filesystem: 'False' - dcp_async_mode_enabled: 'False' - enable_gcs_patch_in_boto3: 'False' - jit: - device: cuda - dtype: bfloat16 - enabled: 'False' - input_shape: null - strict: 'True' - keys_not_to_resume: [] - keys_to_skip_loading: [] - load_ema_to_reg: 'False' - load_from_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - load_path: '' - load_training_state: 'False' - only_load_scheduler_state: 'False' - save_iter: '500' - save_to_object_store: - bucket: bucket - credentials: credentials/s3_checkpoint.secret - enabled: 'True' - strict_resume: 'True' - type: - _target_: - callbacks: null - disable_async: 'False' - verbose: 'True' -dataloader_train: - _target_: - dataloaders: - image_data: - dataloader: - _target_: - batch_size: '2' - cache_augment_fn: null - cache_replay_name: image_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - video_data: - dataloader: - _target_: - batch_size: '1' - cache_augment_fn: null - cache_replay_name: video_dataloader - cache_size: '32' - concat_size: '1' - dataset: - _target_: - len_t5: '512' - num_video_frames: '136' - resolution: '512' - t5_dim: '1024' - num_workers: '8' - pin_memory: 'True' - shuffle: 'False' - use_cache: 'False' - webdataset: 'False' - ratio: '1' - dataset: - augmentor_name: video_basic_augmentor_v2_with_control - caption_type: t2w_qwen2p5_7b - control_input_type: edge - dataset_resolution_type: gt720p - embedding_type: null - max_fps_thres: '60' - min_fps_thres: '10' - num_video_frames: '93' - resolution: '720' - use_native_fps: 'True' - video_decoder_name: video_naive_bytes - num_workers: '4' -dataloader_val: null -defaults: -- _self_ -- data_train: null -- data_val: null -- optimizer: fusedadamw -- scheduler: lambdalinear -- callbacks: basic -- model: ddp -- net: null -- net_fake_score: null -- net_teacher: null -- net_discriminator_head: null -- conditioner: video_prediction_conditioner -- ema: power -- tokenizer: wan2pt1_tokenizer -- checkpoint: s3 -- ckpt_type: dcp_distill -- condition_postprocessor: null -- experiment: null -job: - cluster: null - group: cosmos3_interactive - name: dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge - project: cosmos_interactive - wandb_mode: online -model: - _recursive_: 'False' - _target_: - config: - base_load_from: null - condition_postprocessor: - _target_: - hint_keys: - - edge - conditional_frames_probs: - 0: 0.6 - 1: 0.2 - 2: 0.2 - conditioner: - _target_: - control_input_depth: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth - output_key: control_input_depth - control_input_depth_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_depth_mask - output_key: control_input_depth_mask - control_input_edge: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge - output_key: control_input_edge - control_input_edge_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_edge_mask - output_key: control_input_edge_mask - control_input_inpaint: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint - output_key: control_input_inpaint - control_input_inpaint_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_inpaint_mask - output_key: control_input_inpaint_mask - control_input_seg: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg - output_key: control_input_seg - control_input_seg_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_seg_mask - output_key: control_input_seg_mask - control_input_vis: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis - output_key: control_input_vis - control_input_vis_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: control_input_vis_mask - output_key: control_input_vis_mask - fps: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: fps - output_key: fps - padding_mask: - _target_: - dropout_rate: '0.0' - dtype: null - input_key: padding_mask - output_key: padding_mask - text: - _target_: - credential_path: credentials/s3_training.secret - dropout_rate: '0.2' - empty_string_embeddings_path: s3://bucket/predict2_assets/reason1_empty_string_embeddings.pt - input_key: - - t5_text_embeddings - use_empty_string: 'False' - use_video_condition: - _target_: - dropout_rate: '0.0' - input_key: fps - output_key: use_video_condition - ema: - enabled: false - iteration_shift: 0 - rate: 0.1 - fsdp_shard_size: 1 - grad_clip: true - input_caption_key: ai_caption - input_data_key: video - input_image_key: images - intermediate_feature_ids: null - load_teacher_weights: false - loss_reduce: mean - loss_scale_GAN_discriminator: 1.0 - loss_scale_GAN_generator: 1.0 - loss_scale_fake_score: 1.0 - loss_scale_sid: 1.0 - max_num_conditional_frames: 2 - min_num_conditional_frames: 0 - multiply_noise_by_video_len: true - neg_embed_path: '' - neg_prompt_str: The video captures a game playing, with bad crappy graphics and - cartoonish frames. It represents a recording of old outdated games. The lighting - looks very fake. The textures are very raw and basic. The geometries are very - primitive. The images are very pixelated and of poor CG quality. There are many - subtitles in the footage. Overall, the video is unrealistic at all. - net: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_discriminator_head: null - net_fake_score: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - net_teacher: - _target_: - adaln_lora_dim: '256' - atten_backend: minimal_a2a - concat_padding_mask: 'True' - condition_strategy: spaced - crossattn_emb_channels: '1024' - crossattn_proj_in_channels: '100352' - extra_per_block_abs_pos_emb: 'False' - in_channels: '16' - max_frames: '128' - max_img_h: '240' - max_img_w: '240' - mlp_ratio: '4.0' - model_channels: '2048' - num_blocks: '28' - num_control_branches: '1' - num_heads: '16' - num_max_modalities: '8' - out_channels: '16' - patch_spatial: '2' - patch_temporal: '1' - pos_emb_cls: rope3d - pos_emb_interpolation: crop - pos_emb_learnable: 'True' - rope_enable_fps_modulation: 'False' - rope_h_extrapolation_ratio: '3.0' - rope_t_extrapolation_ratio: '1.0' - rope_w_extrapolation_ratio: '3.0' - sac_config: - every_n_blocks: 1 - mode: predict2_2b_720_aggressive - separate_embedders: 'False' - spatial_compression_factor: '8' - timestep_scale: '1.0' - use_adaln_lora: 'True' - use_after_proj_for_multi_branch: 'True' - use_crossattn_projection: 'True' - use_cuda_graphs: 'False' - use_input_hint_block: 'False' - use_wan_fp32_strategy: 'True' - vace_block_every_n: '7' - vace_has_mask: 'False' - noise_level_parameterization: trigflow - optimizer_discriminator_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - optimizer_fake_score_config: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 2e-07 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' - precision: bfloat16 - rectified_flow_loss_weight_uniform: false - rectified_flow_t_scaling_factor: 1.0 - replace_cond_output_with_gt: true - resolution: '720' - scaling: rectified_flow - sde: - _target_: - p_mean: '-0.8' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - sde_D: - _target_: - p_mean: '0.0' - p_std: '1.6' - sigma_max: '80' - sigma_min: '0.0002' - selected_sampling_time: - - 1.5707963267948966 - - 1.5042281630190728 - - 1.373400766945016 - - 1.0303768265243125 - sigma_conditional: 0.0001 - sigma_data: 1.0 - state_ch: 16 - state_t: 24 - student_load_from: null - student_update_freq: 5 - teacher_guidance: 3.0 - teacher_load_from: - credentials: credentials/s3_checkpoint.secret - load_path: s3://bucket/cosmos_transfer2/vid2vid_2B_control/edge_720p_t24_spaced_layer4_cr1pt1_sdev2_lowsigma0.05_nonuniform_hqv3p1_20250714_64N_rectified_flow/checkpoints/iter_000029000/model - text_encoder_class: reason1p1_7B - text_encoder_config: - ckpt_path: s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/ - compute_online: true - embedding_concat_strategy: full_concat - model_config: - _target_: - model_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenModelConfig - activation_checkpoint: - mode: selective - models: vlm - selective_ac_option: op - add_answer_tag: 'True' - add_cross_attention: 'False' - add_image_start_end_tag: 'False' - add_tile_tag: 'False' - architectures: - - Qwen2_5_VLForConditionalGeneration - attention_dropout: '0.0' - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - aux_loss_coeff: '0.0' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: '151643' - cache_dir: null - checkpoint: - async_mode: disabled - create_seed_checkpoint: false - enable_checkpoint: false - export_dtype: float32 - folder: checkpoint - interval: 500 - interval_type: steps - model_weights_only: false - chunk_size_feed_forward: '0' - ckpt_dir: null - ckpt_path: null - comm: - init_timeout_seconds: 300 - trace_buf_size: 20000 - train_timeout_seconds: 100 - cp_size: null - cross_attention_hidden_size: null - decoder_start_token_id: null - deterministic: 'False' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - encoder_no_repeat_ngram_size: '0' - eos_token_id: '151645' - ep_size: null - experimental: - enable_async_tensor_parallel: false - enable_compiled_autograd: false - pipeline_parallel_degree: 1 - exponential_decay_length_penalty: null - finetuning_task: null - float8: - enable_float8_linear: false - forced_bos_token_id: null - forced_eos_token_id: null - freeze_llm: 'False' - freeze_mm_projector: 'False' - freeze_vision_encoder: 'False' - fsdp_enabled: 'False' - hidden_act: silu - hidden_size: '3584' - id2label: - 0: LABEL_0 - 1: LABEL_1 - image_token_id: '151655' - initializer_range: '0.02' - intermediate_size: '18944' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - loss_per_token: 'True' - max_batch_size: '1' - max_length: '20' - max_position_embeddings: '128000' - max_seq_len: '128000' - max_window_layers: '28' - min_length: '0' - mm_projector: null - model_type: qwen2_5_vl - name_or_path: Qwen/Qwen2.5-VL-7B-Instruct - no_repeat_ngram_size: '0' - num_attention_heads: '28' - num_beam_groups: '1' - num_beams: '1' - num_hidden_layers: '28' - num_key_value_heads: '4' - num_return_sequences: '1' - num_tiles: '1' - optimizer: - early_step_in_backward: false - end_lr: 2.5e-05 - fused: false - init_lr: 1.0e-05 - lr: 0.0003 - lr_multiplier_llm: 1.0 - lr_multiplier_mm_projector: 1.0 - lr_multiplier_vision_encoder: 0.1 - name: AdamW - output_attentions: 'False' - output_hidden_states: 'True' - output_scores: 'False' - pad_token_id: null - precision: bfloat16 - prefix: null - prepend_padding: 'False' - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - rms_norm_eps: 1e-06 - rope_scaling: - mrope_section: - - '16' - - '24' - - '24' - rope_type: default - type: default - rope_theta: '1000000.0' - s3_credential_path: credentials/pbss_dir.secret - seed: '0' - sep_token_id: null - sliding_window: '32768' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'False' - tile_tag_type: space_separated - tokenizer_class: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - training: - compile: false - context_parallel_degree: 1 - data_parallel_replicate_degree: 1 - data_parallel_shard_degree: -1 - disable_loss_parallel: false - enable_cpu_offload: false - fsdp_reshard_after_forward: default - mixed_precision_param: bfloat16 - mixed_precision_reduce: float32 - steps: 400000 - tensor_parallel_degree: 1 - use_cosine_decay: false - use_linear_decay: true - warmup_steps: 1000 - training_seq_len: '4096' - transformers_version: 4.51.0.dev0 - typical_p: '1.0' - use_bfloat16: 'False' - use_cache: 'False' - use_fsdp2: 'True' - use_return_dict: 'True' - use_rope_from_torchtitan: 'False' - use_sliding_window: 'False' - video_token_id: '151656' - vision_config: - _target_: cosmos_transfer2._src.reason1.configs.default.model_config_qwen.QwenVisionConfig - add_cross_attention: 'False' - architectures: null - attn_implementation: flash_attention_2 - attn_implementation_autoset: 'True' - bad_words_ids: null - begin_suppress_tokens: null - bos_token_id: null - chunk_size_feed_forward: '0' - cross_attention_hidden_size: null - decoder_start_token_id: null - depth: '32' - diversity_penalty: '0.0' - do_sample: 'False' - early_stopping: 'False' - embed_dim: null - encoder_no_repeat_ngram_size: '0' - eos_token_id: null - exponential_decay_length_penalty: null - finetuning_task: null - forced_bos_token_id: null - forced_eos_token_id: null - fullatt_block_indexes: - - '7' - - '15' - - '23' - - '31' - hidden_act: silu - hidden_size: '1280' - id2label: - 0: LABEL_0 - 1: LABEL_1 - in_channels: '3' - in_chans: '3' - intermediate_size: '3420' - is_decoder: 'False' - is_encoder_decoder: 'False' - label2id: - LABEL_0: '0' - LABEL_1: '1' - length_penalty: '1.0' - max_length: '20' - min_length: '0' - mlp_ratio: null - model_type: qwen2_5_vl - name_or_path: '' - no_repeat_ngram_size: '0' - num_beam_groups: '1' - num_beams: '1' - num_heads: '16' - num_return_sequences: '1' - out_hidden_size: '3584' - output_attentions: 'False' - output_hidden_states: 'False' - output_scores: 'False' - pad_token_id: null - patch_size: '14' - prefix: null - problem_type: null - pruned_heads: _Nothing.NOTHING - remove_invalid_values: 'False' - repetition_penalty: '1.0' - return_dict: 'True' - return_dict_in_generate: 'False' - sep_token_id: null - spatial_merge_size: '2' - spatial_patch_size: '14' - suppress_tokens: null - task_specific_params: null - temperature: '1.0' - temporal_patch_size: '2' - tf_legacy_loss: 'False' - tie_encoder_decoder: 'False' - tie_word_embeddings: 'True' - tokenizer_class: null - tokens_per_second: '2' - top_k: '50' - top_p: '1.0' - torch_dtype: bfloat16 - torchscript: 'False' - typical_p: '1.0' - use_bfloat16: 'False' - window_size: '112' - vision_encoder: openai/clip-vit-base-patch32 - vision_encoder_config: - depth_init: true - dim: 1024 - ffn_dim_multiplier: null - head_dim: null - hidden_act: null - hidden_dim: 4096 - image_size: 1024 - image_token_id: null - multiple_of: null - n_heads: 16 - n_kv_heads: null - n_layers: 24 - norm_eps: 1.0e-05 - norm_type: rmsnorm - num_channels: 3 - patch_size: 16 - proj_bias: null - qkv_bias: null - rope_theta: 10000.0 - use_cache: false - use_rope_from_torchtitan: false - vision_encoder_in_channels: '3' - vision_end_token_id: '151653' - vision_start_token_id: '151652' - vision_token_id: '151654' - vocab_size: '152064' - z_loss_coeff: '0.0' - tokenizer: - _target_: - cache_dir: null - tokenizer_type: Qwen/Qwen2.5-VL-7B-Instruct - n_layers_per_group: 5 - s3_credential_path: credentials/s3_checkpoint.secret - timestep_shift: 5.0 - tokenizer: - _target_: - chunk_duration: '81' - load_mean_std: 'False' - name: wan2pt1_tokenizer - use_clean_cond_timesteps: true - use_neg_prompt_str: false - use_torch_compile: false - vis_debug: false - warmup_steps: 1 -model_parallel: - _cpu_offloading_context: null - async_tensor_model_parallel_allreduce: false - autocast_dtype: torch.float32 - barrier_with_L1_time: true - batch_p2p_comm: true - batch_p2p_sync: true - bf16: false - context_parallel_size: 4 - cpu_offloading: false - cpu_offloading_activations: true - cpu_offloading_double_buffering: false - cpu_offloading_num_layers: 0 - cpu_offloading_weights: true - cross_entropy_fusion_impl: native - cross_entropy_loss_fusion: false - deallocate_pipeline_outputs: false - defer_embedding_wgrad_compute: false - delay_wgrad_compute: false - deterministic_mode: false - enable_autocast: false - expert_model_parallel_size: 1 - expert_tensor_parallel_size: 1 - finalize_model_grads_func: null - fp16: false - grad_scale_func: null - grad_sync_func: null - gradient_accumulation_fusion: false - hierarchical_context_parallel_sizes: null - microbatch_group_size_per_vp_stage: 1 - moe_extended_tp: false - no_sync_func: null - num_microbatches_with_partial_activation_checkpoints: null - overlap_moe_expert_parallel_comm: false - overlap_p2p_comm: false - overlap_p2p_comm_warmup_flush: false - param_sync_func: null - params_dtype: torch.float32 - perform_initialization: true - pipeline_dtype: null - pipeline_model_parallel_comm_backend: null - pipeline_model_parallel_size: 1 - sequence_parallel: false - tensor_model_parallel_size: 1 - timers: null - tp_comm_atomic_ag: false - tp_comm_atomic_rs: false - tp_comm_bootstrap_backend: nccl - tp_comm_bulk_dgrad: true - tp_comm_bulk_wgrad: true - tp_comm_overlap: false - tp_comm_overlap_ag: true - tp_comm_overlap_disable_fc1: false - tp_comm_overlap_disable_qkv: false - tp_comm_overlap_rs: true - tp_comm_overlap_rs_dgrad: false - tp_comm_split_ag: true - tp_comm_split_rs: true - use_cpu_initialization: false - use_ring_exchange_p2p: false - use_te_rng_tracker: false - variable_seq_lengths: false - virtual_pipeline_model_parallel_size: null - wgrad_deferral_limit: 0 -optimizer: - _target_: - betas: - - '0.9' - - '0.999' - capturable: 'True' - eps: 1e-08 - lr: 1e-06 - master_weights: 'True' - model: null - optim_type: fusedadam - weight_decay: '0.01' -scheduler: - _target_: - cycle_lengths: - - '400000' - f_max: - - '0.99' - f_min: - - '0.4' - f_start: - - 1e-06 - verbosity_interval: '0' - warm_up_steps: - - '100' -trainer: - callbacks: - compile_tokenizer: - _target_: - compile_after_iterations: '4' - dynamic: 'False' - enabled: 'True' - dataloader_speed: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - device_monitor: - _target_: - every_n: '10' - log_memory_detail: 'True' - save_s3: 'True' - step_size: '1' - upload_every_n_mul: '10' - every_n_sample_ema: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'True' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - every_n_sample_reg: - _target_: - do_sample_val_prompts: 'True' - every_n: '250' - is_ema: 'False' - is_image: 'False' - is_sample: 'True' - n_sample_to_save: '128' - num_prompts: '4' - num_samples_per_prompt: '3' - num_sampling_step: '4' - num_sampling_step_teacher: '35' - save_s3: 'True' - show_all_frames: 'False' - step_size: '1' - use_negative_prompt: 'False' - grad_clip: - _target_: - clip_norm: '1.0' - force_finite: 'True' - heart_beat: - _target_: - every_n: '10' - save_s3: 'True' - step_size: '1' - update_interval_in_minute: '20' - iter_speed: - _target_: - every_n: '10' - hit_thres: '100' - save_s3: 'True' - save_s3_every_log_n: '10' - low_prec: - _target_: - config: null - trainer: null - update_iter: '1' - manual_gc: - _target_: - every_n: '5' - warm_up: '5' - wandb: - _target_: - logging_iter_multipler: '1' - save_logging_iter_multipler: '10' - save_s3: 'True' - wandb_10x: - _target_: - logging_iter_multipler: '10' - save_logging_iter_multipler: '1' - save_s3: 'True' - compile_config: - recompile_limit: '8' - use_duck_shape: 'True' - cudnn: - benchmark: 'True' - deterministic: 'False' - ddp: - broadcast_buffers: 'True' - find_unused_parameters: 'False' - static_graph: 'True' - distributed_parallelism: fsdp - grad_accum_iter: '1' - grad_scaler_args: - enabled: 'False' - logging_iter: '10' - max_iter: '30000' - max_val_iter: null - memory_format: torch.preserve_format - profiling: - enable_memory_snapshot: 'False' - enable_profiling: 'False' - profile_freq: '1' - profile_memory: 'False' - record_shape: 'False' - save_s3: 'False' - target_ranks: - - '0' - - '1' - - '2' - - '3' - - '4' - - '5' - - '6' - - '7' - with_modules: 'True' - with_stack: 'True' - run_validation: 'False' - run_validation_on_start: 'False' - seed: '0' - straggler_detection: - analyze_backward: 'True' - analyze_dataloading: 'True' - analyze_forward: 'True' - analyze_optimizer: 'True' - enabled: 'False' - max_diff: '2.0' - profile_freq: '1' - raise_error: 'True' - report_freq: '100' - timeout_period: '999999999' - type: - validation_iter: '100' -upload_reproducible_setup: 'True' diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/console.log b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/console.log deleted file mode 100644 index 2f00b69678ff8eceedb9cc0b243872f39013fbcb..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/console.log +++ /dev/null @@ -1,22 +0,0 @@ -[06-21 13:16:59|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 13:16:59|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 13:17:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:17:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:17:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:17:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:17:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:17:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:17:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 13:17:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:139:__init__] Setting net_fake_score to None for distilled model inference -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:146:__init__] Found 1 hint keys across all samples -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:156:__init__] Saved config to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/config.yaml -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:163:generate] Generating 1 samples: ['sunny_weather_distilled_step4_bg0.5_rm1'] -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_distilled_step4_bg0.5_rm1 -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.json -[06-21 13:17:09|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:18:15|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 13:18:16|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 -[06-21 13:18:16|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:18:18|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/debug.log b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/debug.log deleted file mode 100644 index fbae1533ee669c31782e8a893a3eaaad21ac4213..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/debug.log +++ /dev/null @@ -1,1484 +0,0 @@ -[06-21 13:16:47|DEBUG|packages/cosmos-oss/cosmos_oss/init.py:176:init_output_dir] Flags(internal=False, training=True, smoke=False, verbose=False, experimental_checkpoints=True) -[06-21 13:16:48|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:16:48|DEBUG|cosmos_transfer2/_src/imaginaire/utils/env_parsers/env_parser.py:86:get_val_dict] getting val dict of CredentialEnvParser -[06-21 13:16:58|CRITICAL|cosmos_transfer2/_src/interactive/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:16:58|CRITICAL|cosmos_transfer2/_src/predict2/checkpointer/dcp.py:181:] for the back comptiable pytorch! New DefaultLoadPlanner class is created. -[06-21 13:16:59|DEBUG|cosmos_transfer2/inference.py:46:__init__] SetupArguments(output_dir=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1') model='edge/distilled' checkpoint_path='s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000' experiment='dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge' config_file='cosmos_transfer2/_src/interactive/configs/registry_transfer2p5.py' context_parallel_size=1 disable_guardrails=True offload_guardrail_models=False keep_going=True profile=False benchmark=False compile_tokenizer= enable_parallel_tokenizer=False parallel_tokenizer_grid=(-1, -1))(['edge']) -[06-21 13:16:59|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] Flash Attention v3 is not supported because the Python package ('flash_attn_3_nv'_) was not found. -[06-21 13:16:59|DEBUG|cosmos_transfer2/_src/imaginaire/attention/utils/safe_log.py:35:debug] NATTEN Attention is not supported due to insufficient NATTEN version 0.21.0, expected at least 0.21.5.dev9. -[06-21 13:16:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1... -[06-21 13:16:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2... -[06-21 13:16:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor... -[06-21 13:16:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v1_with_control... -[06-21 13:16:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control... -[06-21 13:16:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering image_basic_augmentor_with_control... -[06-21 13:16:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_v2_with_control_and_image_context... -[06-21 13:16:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering video_basic_augmentor_with_control_input... -[06-21 13:16:59|INFO|cosmos_transfer2/_src/transfer2/datasets/augmentor_provider.py:35:augmentor_register] registering hdmap_augmentor_for_local_datasets... -[06-21 13:16:59|CRITICAL|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:192:import_all_modules_from_package] Reloading all modules from package cosmos_transfer2._src.interactive.configs.registry_experiment -[06-21 13:16:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiment_list -[06-21 13:16:59|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_ac_predict2p5 -[06-21 13:16:59|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Predict2.5-2B/robot/action-cond(38c6c645-7d41-4560-8eeb-6f4ddc0e6574) -[06-21 13:16:59|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision main robot/action-cond/38c6c645-7d41-4560-8eeb-6f4ddc0e6574_ema_bf16.pt -[06-21 13:17:00|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_predict2p5 -[06-21 13:17:00|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_dmd2_transfer2p5 -[06-21 13:17:00|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_knowledge_distill_ac_predict2p5 -[06-21 13:17:00|DEBUG|cosmos_transfer2/_src/imaginaire/utils/config_helper.py:210:import_modules_recursively] Reloading module cosmos_transfer2._src.interactive.configs.registry_experiment.experiments_self_forcing_ac_predict2p5 -[06-21 13:17:00|INFO|cosmos_transfer2/_src/imaginaire/utils/misc.py:151:set_random_seed] Using random seed 0. -[06-21 13:17:00|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:81:load_model_from_checkpoint] Loading model from s3://bucket/cosmos_interactive_fastgen/cosmos_interactive/cosmos_fastgen_dmd2_trigflow_distill_cosmos_transfer2p5_2B_bidirectional_edge_bugfix_v2/checkpoints/iter_000010000 -[06-21 13:17:00|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:109:load_model_from_checkpoint] Setting load_teacher_weights=False for inference to skip teacher checkpoint download -[06-21 13:17:00|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:94:__init__] Setting precision to torch.bfloat16 -[06-21 13:17:00|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:74:__init__] Instantiating text encoder model... -[06-21 13:17:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Qwen/Qwen2.5-VL-7B-Instruct(7219c6c7-f878-4137-bbdb-76842ea85e70) -[06-21 13:17:00|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:17:01|INFO|cosmos_transfer2/_src/reason1/tokenizer/processor.py:75:__init__] Successfully loaded processor from local cache -[06-21 13:17:01|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:116:__init__] Setting torch default dtype from torch.float32 to torch.bfloat16 -[06-21 13:17:01|INFO|cosmos_transfer2/_src/reason1/models/vlm_base.py:123:__init__] Reset torch default dtype to torch.float32 -[06-21 13:17:01|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:84:__init__] Loading checkpoint from s3://bucket/cosmos_reasoning1/sft_exp700/sft_exp721-1_qwen7b_tl_721_5vs5_s3_balanced_n32_resume_16k/checkpoints/iter_000016000/model/. -[06-21 13:17:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Reason1.1-7B(cb3e3ffa-7b08-4c34-822d-61c7aa31a14f) -[06-21 13:17:01|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Reason1-7B --repo-type model --revision 3210bec0495fdc7a8d3dbb8d58da5711eab4b423 --include '*' -[06-21 13:17:05|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:113:__init__] Finished loading checkpoint from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Reason1-7B/snapshots/3210bec0495fdc7a8d3dbb8d58da5711eab4b423. -[06-21 13:17:05|INFO|cosmos_transfer2/_src/predict2/text_encoders/text_encoder.py:116:__init__] Text encoder model instantiated -[06-21 13:17:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint Wan2.1/vae(685afcaa-4de2-42fe-b7b9-69f7a2dee4d8) -[06-21 13:17:05|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Predict2.5-2B --repo-type model --revision f176dc95b4a70f53ce01c4b302851595e7322b00 tokenizer.pth -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/tokenizers/wan2pt1.py:669:_video_vae] loading /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2.5-2B/snapshots/f176dc95b4a70f53ce01c4b302851595e7322b00/tokenizer.pth -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:17:06|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.67 s -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #0-fps: - ReMapkey - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: fps - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #1-padding_mask: - ReMapkey - input key: padding_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: padding_mask - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #2-text: - TextAttr - input key: ['t5_text_embeddings'] - Param count: 0 - Trainable: None - Dropout rate: 0.2 - Output key: [crossattn_emb] -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #3-use_video_condition: - BooleanFlag - input key: fps - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: use_video_condition - This is a boolean flag -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #4-control_input_edge: - ReMapkey - input key: control_input_edge - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #5-control_input_vis: - ReMapkey - input key: control_input_vis - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #6-control_input_depth: - ReMapkey - input key: control_input_depth - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #7-control_input_seg: - ReMapkey - input key: control_input_seg - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #8-control_input_inpaint: - ReMapkey - input key: control_input_inpaint - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #9-control_input_edge_mask: - ReMapkey - input key: control_input_edge_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_edge_mask - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #10-control_input_vis_mask: - ReMapkey - input key: control_input_vis_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_vis_mask - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #11-control_input_depth_mask: - ReMapkey - input key: control_input_depth_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_depth_mask - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #12-control_input_seg_mask: - ReMapkey - input key: control_input_seg_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_seg_mask - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/predict2/conditioner.py:434:__init__] Initialized embedder #13-control_input_inpaint_mask: - ReMapkey - input key: control_input_inpaint_mask - Param count: 0 - Trainable: None - Dropout rate: 0.0 - Output key: control_input_inpaint_mask - Dtype: None -[06-21 13:17:06|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:231:build_model] - -==============config condition_postprocessor: {'hint_keys': ['edge'], '_target_': } -[06-21 13:17:06|INFO|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:232:build_model] - -==============condition_postprocessor: -[06-21 13:17:06|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_model: 6.43 s -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:06|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1624:build_pos_embed] Building positional embedding with rope3d class, impl -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:886:__init__] Using AdaLN LoRA Flag: True. We enable bias if no AdaLN LoRA for backward compatibility. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:17:07|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is None and using 16 heads with a dimension of 128. -[06-21 13:17:07|DEBUG|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:432:__init__] Setting up Attention. Query dim is 2048, context_dim is 1024 and using 16 heads with a dimension of 128. -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 28 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 4 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 5 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 6 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 7 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 8 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 9 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 10 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 11 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 12 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 13 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 14 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 15 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 16 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 17 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 18 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 19 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 20 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 21 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 22 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 23 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 24 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 25 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 26 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 27 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1804:enable_selective_checkpoint] Enable selective checkpoint with predict2_2b_720_aggressive, for every 1 blocks. Total blocks: 4 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 0 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 1 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 2 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/predict2/networks/minimal_v4_dit.py:1810:enable_selective_checkpoint] Enable selective checkpoint for block 3 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on Cosmos2InteractiveModel: build_net: 0.65 s -[06-21 13:17:08|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:86:build_model] ==========Instantiating networks...========== -[06-21 13:17:08|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:87:build_model] net: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:17:08|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:88:build_model] net_teacher: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:17:08|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:89:build_model] net_fake_score: MinimalV4LVGControlVaceDiT( - (x_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=72, out_features=2048, bias=False) - ) - ) - (pos_embedder): VideoRopePosition3DEmb() - (t_embedder): Sequential( - (0): Timesteps() - (1): TimestepEmbedding( - (linear_1): Linear(in_features=2048, out_features=2048, bias=False) - (activation): SiLU() - (linear_2): Linear(in_features=2048, out_features=6144, bias=False) - ) - ) - (blocks): ModuleList( - (0-27): 28 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlAwareDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - ) - ) - ) - (final_layer): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): CheckpointWrapper( - (_checkpoint_wrapped_module): FinalLayer( - (layer_norm): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (linear): Linear(in_features=2048, out_features=64, bias=False) - (adaln_modulation): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=4096, bias=False) - ) - ) - ) - ) - ) - (t_embedding_norm): RMSNorm() - (crossattn_proj): Sequential( - (0): Linear(in_features=100352, out_features=1024, bias=True) - (1): GELU(approximate='none') - ) - (control_embedder): PatchEmbed( - (proj): Sequential( - (0): Rearrange('b c (t r) (h m) (w n) -> b t h w (c r m n)', r=1, m=2, n=2) - (1): Linear(in_features=520, out_features=2048, bias=False) - ) - ) - (control_blocks): ModuleList( - (0): CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (before_proj): Linear(in_features=2048, out_features=2048, bias=True) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - (1-3): 3 x CheckpointWrapper( - (_checkpoint_wrapped_module): ControlEncoderDiTBlock( - (layer_norm_self_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (self_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=2048, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=2048, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_cross_attn): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (cross_attn): Attention( - (q_proj): Linear(in_features=2048, out_features=2048, bias=False) - (q_norm): RMSNorm() - (k_proj): Linear(in_features=1024, out_features=2048, bias=False) - (k_norm): RMSNorm() - (v_proj): Linear(in_features=1024, out_features=2048, bias=False) - (v_norm): Identity() - (output_proj): Linear(in_features=2048, out_features=2048, bias=False) - (output_dropout): Identity() - (attn_op): MinimalA2AAttnOp() - ) - (layer_norm_mlp): LayerNorm((2048,), eps=1e-06, elementwise_affine=False) - (mlp): GPT2FeedForward( - (activation): GELU(approximate='none') - (layer1): Linear(in_features=2048, out_features=8192, bias=False) - (layer2): Linear(in_features=8192, out_features=2048, bias=False) - ) - (adaln_modulation_self_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_cross_attn): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (adaln_modulation_mlp): Sequential( - (0): SiLU() - (1): Linear(in_features=2048, out_features=256, bias=False) - (2): Linear(in_features=256, out_features=6144, bias=False) - ) - (after_proj): Linear(in_features=2048, out_features=2048, bias=True) - ) - ) - ) -) -[06-21 13:17:08|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:128:build_model] Freezing the CR1 embedding projection layer in student net.. -[06-21 13:17:08|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:132:build_model] Freezing the CR1 embedding projection layer in fake score net.. -[06-21 13:17:08|INFO|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:135:build_model] Freezing teacher net.. -[06-21 13:17:08|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:119:setup_loss_specs] Using mean loss reduce with loss scale 1.0 -[06-21 13:17:08|INFO|cosmos_transfer2/_src/imaginaire/utils/timer.py:150:_log] Time spent on instantiate model: 7.78 s -[06-21 13:17:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:297:download] Downloading checkpoint nvidia/Cosmos-Transfer2.5-2B/distilled/edge(41f07f13-f2e4-4e34-ba4c-86f595acbc20) -[06-21 13:17:08|INFO|cosmos_transfer2/_src/imaginaire/utils/checkpoint_db.py:165:_hf_download] uvx 'hf>=1.3.5' download nvidia/Cosmos-Transfer2.5-2B --repo-type model --revision bbaeedb2b57cc8b14a44653099e2551adb69dcc7 distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 13:17:08|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:214:load_model_state_dict_from_checkpoint] Loading model cached locally from /scratch/ssaha/.cache/huggingface/hub/models--nvidia--Cosmos-Transfer2.5-2B/snapshots/bbaeedb2b57cc8b14a44653099e2551adb69dcc7/distilled/general/edge/41f07f13-f2e4-4e34-ba4c-86f595acbc20_ema_bf16.pt -[06-21 13:17:09|INFO|cosmos_transfer2/_src/interactive/utils/model_loader.py:173:_process_pt_state_dict_for_ema] Loading EMA-exported checkpoint with net.* keys directly -[06-21 13:17:09|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:408:load_state_dict] load model in non-strict mode -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 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blocks.25.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.25.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.26.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key blocks.27.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key t_embedding_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.0.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.1.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.2.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.self_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.q_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|WARNING|cosmos_transfer2/_src/imaginaire/utils/checkpointer.py:451:non_strict_load_model] Skipping key control_blocks.3.cross_attn.k_norm._extra_state introduced by TransformerEngine for FP8 in the checkpoint. -[06-21 13:17:09|CRITICAL|cosmos_transfer2/_src/interactive/methods/cosmos2_interactive_model.py:409:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=[], unexpected_keys=[], incorrect_shapes=[]) -[06-21 13:17:09|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:819:load_state_dict] load fake score model in non-strict mode -[06-21 13:17:09|CRITICAL|cosmos_transfer2/_src/interactive/methods/distribution_matching/dmd2.py:820:load_state_dict] [RANK 0] _IncompatibleKeys(missing_keys=['accum_video_sample_counter', 'accum_image_sample_counter', 'accum_iteration', 'accum_train_in_hours', 'x_embedder.proj.1.weight', 'pos_embedder.seq', 'pos_embedder.dim_spatial_range', 'pos_embedder.dim_temporal_range', 't_embedder.1.linear_1.weight', 't_embedder.1.linear_2.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.0._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.0._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.0._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.1._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.1._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.1._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.2._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.2._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.2._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.q_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.k_norm.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.v_proj.weight', 'blocks.3._checkpoint_wrapped_module.cross_attn.output_proj.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer1.weight', 'blocks.3._checkpoint_wrapped_module.mlp.layer2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_self_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_cross_attn.2.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.1.weight', 'blocks.3._checkpoint_wrapped_module.adaln_modulation_mlp.2.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.q_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.k_norm.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.v_proj.weight', 'blocks.4._checkpoint_wrapped_module.self_attn.output_proj.weight', 'blocks.4._checkpoint_wrapped_module.cross_attn.q_proj.weight', 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['sunny_weather_distilled_step4_bg0.5_rm1'] -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:167:generate] [1/1] Processing sample sunny_weather_distilled_step4_bg0.5_rm1 -[06-21 13:17:09|DEBUG|cosmos_transfer2/inference.py:186:_generate_sample] InferenceArguments(name='sunny_weather_distilled_step4_bg0.5_rm1' prompt_path=None prompt='The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.' negative_prompt='The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.' seed=2025 guidance=3 video_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4') max_frames=None context_frame_index=None image_context_path=None num_conditional_frames=1 resolution='720' sigma_max=None num_video_frames_per_chunk=93 num_steps=4 show_control_condition=False show_input=False keep_input_resolution=True edge=EdgeConfig(control_path=PosixPath('/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4'), control_weight=1.0, mask_path=None, mask_prompt=None, preset_edge_threshold='medium') depth=None vis=None seg=None guided_generation_mask=None guided_generation_step_threshold=25 guided_generation_foreground_labels=None) -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:208:_generate_sample] Saved arguments to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.json -[06-21 13:17:09|WARNING|cosmos_transfer2/inference.py:239:_generate_sample] Guardrail checks on prompt are disabled -[06-21 13:17:09|INFO|cosmos_transfer2/inference.py:242:_generate_sample] Processing the following paths: {'edge': '/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4', 'edge_mask': None, 'edge_mask_prompt': None} -[06-21 13:17:09|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:472:generate_img2world] Loading input video... -[06-21 13:17:09|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4 -[06-21 13:17:09|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:17:09|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:492:generate_img2world] Computing prompt text embeddings... -[06-21 13:17:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:513:generate_img2world] Processing image context if available... -[06-21 13:17:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:330:read_and_process_image_context] No image context provided. -[06-21 13:17:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:525:generate_img2world] Loading control inputs... -[06-21 13:17:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:204:read_video_or_image_into_frames_BCTHW] Reading video from /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4 -[06-21 13:17:10|INFO|cosmos_transfer2/_src/transfer2/inference/utils.py:243:read_video_or_image_into_frames_BCTHW] Loaded input tensor with shape (1, 3, 120, 720, 1280) value 0, 255 -[06-21 13:17:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 1/2 -[06-21 13:17:10|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 584845 -[06-21 13:17:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:554:generate_img2world] Generating chunk 2/2 -[06-21 13:17:47|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:640:generate_img2world] Seed: 643774 -[06-21 13:18:15|INFO|cosmos_transfer2/_src/transfer2/inference/inference_pipeline.py:736:generate_img2world] Average time per chunk: 31.70261830254458 -[06-21 13:18:15|WARNING|cosmos_transfer2/inference.py:299:_generate_sample] Generated output has 120 frames (> 93). The distilled Transfer 2.5 model is not trained to support auto-regressive generation -[06-21 13:18:15|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:18:16|INFO|cosmos_transfer2/inference.py:311:_generate_sample] edge control video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 -[06-21 13:18:16|WARNING|cosmos_transfer2/inference.py:335:_generate_sample] Guardrail checks on video are disabled -[06-21 13:18:16|DEBUG|cosmos_transfer2/_src/imaginaire/utils/easy_io/handlers/imageio_video_handler.py:163:dump_to_fileobj] mimsave_kwargs: {'fps': 10, 'quality': 5, 'macro_block_size': 1, 'ffmpeg_params': ['-s', '1280x720'], 'output_params': ['-f', 'mp4']} -[06-21 13:18:18|SUCCESS|cosmos_transfer2/inference.py:343:_generate_sample] Generated video saved to /scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.mp4 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/spec.json b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/spec.json deleted file mode 100644 index 4e2fada99896465fb73350cbca047f4bf20ff96a..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/spec.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "name": "sunny_weather_distilled_step4_bg0.5_rm1", - "prompt": "The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.", - "video_path": "/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4", - "guidance": 3, - "num_steps": 4, - "seed": 2025, - "edge": { - "control_path": "/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4", - "control_weight": 1.0 - }, - "negative_prompt": "The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows." -} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.json b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.json deleted file mode 100644 index 4b2137d15155d17afb9cdecfad58d3609ef21e76..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.json +++ /dev/null @@ -1 +0,0 @@ -{"name":"sunny_weather_distilled_step4_bg0.5_rm1","prompt_path":null,"prompt":"The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail.","negative_prompt":"The video captures a game playing, with bad crappy graphics and cartoonish frames. It represents a recording of old outdated games. The lighting looks very fake. The textures are very raw and basic. The geometries are very primitive. The images are very pixelated and of poor CG quality. There are many subtitles in the footage. Overall, the video is unrealistic at all. Overcast, rain, wet road, puddles, fog, night, dark shadows.","seed":2025,"guidance":3,"video_path":"/scratch/ssaha/cosmos-transfer2.5/SceneDriveBench/output/priority_from_right/run_000/videos/rgb_front.mp4","max_frames":null,"context_frame_index":null,"image_context_path":null,"num_conditional_frames":1,"resolution":"720","sigma_max":null,"num_video_frames_per_chunk":93,"num_steps":4,"show_control_condition":false,"show_input":false,"keep_input_resolution":true,"edge":{"control_path":"/scratch/ssaha/cosmos-transfer2.5/outputs/edge_threshold_grid/_edges/sunny/edge_bg0.5_rm1.mp4","control_weight":1.0,"mask_path":null,"mask_prompt":null,"preset_edge_threshold":"medium"},"depth":null,"vis":null,"seg":null,"guided_generation_mask":null,"guided_generation_step_threshold":25,"guided_generation_foreground_labels":null} \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.mp4 b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.mp4 deleted file mode 100644 index 960fe843f2f4b20436ecaf5802c50a6d6a862ef9..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:56f43c04082376a35ac290274178701535ff8f16540d47737635eebfabd61ce0 -size 3354665 diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.txt b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.txt deleted file mode 100644 index 464b6055f679cb63d0db8e54bd910217c87b403b..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1.txt +++ /dev/null @@ -1 +0,0 @@ -The video shows an urban intersection captured from a vehicle-mounted camera on a brilliant clear sunny day. A deep blue cloudless sky sits over the scene, warm directional sunlight casts long crisp shadows across the dry asphalt, and the painted lane markings, stop lines and pedestrian crosswalks are bright and high-contrast. Multiple vehicles move through the junction, low-rise buildings, sidewalks, parked cars and street lamps line the streets, and the camera follows the moving ego vehicle smoothly. Photorealistic, cinematic daylight, high detail. \ No newline at end of file diff --git a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 b/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 deleted file mode 100644 index a7e58d7f057ee0f0db3dd0132c780ecd3d41a7e8..0000000000000000000000000000000000000000 --- a/edge_threshold_grid/sunny/weather/distilled_step4_bg0.5_rm1/sunny_weather_distilled_step4_bg0.5_rm1_control_edge.mp4 +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:7a99f3639d51bc435cf50318e1c689dd0c653511fe4a724911e93c08403523ea -size 1859428