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| # Training Config | |
| ```yaml | |
| policy: | |
| name: acp | |
| _target_: force_il.policies.acp.ACPPolicy | |
| action_dim: 19 | |
| pred_horizon: 16 | |
| obs_horizon: 2 | |
| action_horizon: 16 | |
| vision_encoder_name: vit_base_patch32_clip_224.openai | |
| vision_pretrained: true | |
| vision_output_dim: 768 | |
| wrench_encoding: causalconv | |
| wrench_window_size: 256 | |
| wrench_freq: 5000.0 | |
| wrench_output_dim: 384 | |
| fuse_mode: modality-attention | |
| obs_num_rgb_frames: 2 | |
| include_low_dim: true | |
| low_dim_eef_pos_horizon: 3 | |
| low_dim_eef_pos_dim: 3 | |
| low_dim_eef_rot_horizon: 3 | |
| low_dim_eef_rot_dim: 6 | |
| num_diffusion_steps: 50 | |
| noise_scheduler: ddim | |
| unet_down_dims: | |
| - 256 | |
| - 512 | |
| - 1024 | |
| diffusion_step_embed_dim: 32 | |
| unet_kernel_size: 5 | |
| unet_n_groups: 8 | |
| cond_predict_scale: true | |
| input_perturbation: 0.1 | |
| unified_action: true | |
| unified_action_dim: 19 | |
| pose_dim: 9 | |
| vt_dim: 9 | |
| stiffness_dim: 1 | |
| predict_virtual_target: false | |
| predict_stiffness: false | |
| default_stiffness: 100.0 | |
| num_inference_steps: 16 | |
| task: | |
| name: flip_up | |
| dataset_path: data/flip_up_230/flip_up_new_v5 | |
| action_dim: 19 | |
| obs_horizon: 2 | |
| eef_obs_horizon: 3 | |
| eef_down_sample_steps: 5 | |
| pred_horizon: 16 | |
| action_horizon: 16 | |
| action_down_sample_steps: 50 | |
| wrench_horizon: 32 | |
| wrench_down_sample_steps: 4 | |
| query_down_sample_steps: 8 | |
| image_size: 224 | |
| val_ratio: 0.05 | |
| data: | |
| _target_: force_il.data.acp_dataset.ACPEpisodeDataset | |
| dataset_path: data/flip-20e_acp | |
| pred_horizon: 16 | |
| obs_horizon: 2 | |
| rgb_down_sample_steps: 10 | |
| eef_obs_horizon: 3 | |
| eef_down_sample_steps: 5 | |
| action_down_sample_steps: 50 | |
| wrench_horizon: 32 | |
| wrench_down_sample_steps: 4 | |
| query_down_sample_steps: 8 | |
| image_size: 224 | |
| val_ratio: 0.05 | |
| seed: 42 | |
| is_val: false | |
| relative_actions: true | |
| train: | |
| epochs: 300 | |
| batch_size: 128 | |
| gradient_accumulation: 1 | |
| optimizer: | |
| _target_: torch.optim.AdamW | |
| lr: 0.0003 | |
| weight_decay: 1.0e-06 | |
| betas: | |
| - 0.95 | |
| - 0.999 | |
| scheduler: | |
| type: cosine | |
| warmup_steps: 2000 | |
| min_lr: 1.0e-06 | |
| encoder_lr_scale: 0.1 | |
| mixed_precision: fp16 | |
| use_ema: true | |
| ema_decay: 0.9999 | |
| ema_power: 0.75 | |
| ema_update_after_step: 0 | |
| log_interval: 50 | |
| use_wandb: true | |
| wandb_project: force_il | |
| wandb_name: null | |
| val_every: 5 | |
| sample_every: 5 | |
| val_interval: 500 | |
| checkpoint_interval: 10 | |
| save_best: true | |
| best_checkpoint_monitor: train_loss | |
| num_workers: 8 | |
| pin_memory: true | |
| prefetch_factor: 2 | |
| normalizer_use_full_dataset: false | |
| upload_to_hf: true | |
| hf_repo_id: tangPR/acp-flip-up | |
| hf_upload_interval: 100 | |
| seed: 42 | |
| experiment_name: acp_flip_up | |
| seed: 42 | |
| validate: | |
| checkpoint: null | |
| num_samples: 5 | |
| output_dir: ./validation_plots | |
| use_train_split: false | |
| output_dir: outputs/2026-03-23/acp_flip_up_205858 | |
| checkpoint_dir: outputs/2026-03-23/acp_flip_up_205858/checkpoints | |
| log_dir: outputs/2026-03-23/acp_flip_up_205858/logs | |
| ``` | |