PrismWAM / robotwin /config.yaml
MiniWan's picture
Use current module names in model configs and checkpoint metadata; link the paper
c7eca00 verified
Raw History Blame Contribute Delete
3.29 kB
model:
_target_: prismwam.models.wan22.rgb_depth_action_depth_parent.create_prismwam_rgb_depth_action
model_id: Wan-AI/Wan2.2-TI2V-5B
tokenizer_model_id: Wan-AI/Wan2.1-T2V-1.3B
tokenizer_max_len: 128
load_text_encoder: false
redirect_common_files: true
architecture_name: PrismWAM
rgb_input_size:
- 384
- 320
rgb_target_mode: f8
rgb_depth_attention_mode: rgb_to_depth_to_action
rgb_fast: true
rgb_history_num_frames: 5
rgb_history_frame_stride: 4
share_rgb_depth_blocks: true
video_use_text_embedding: true
proprio_dim: 14
mot_checkpoint_mixed_attn: true
skip_depth_dit_load_from_pretrain: true
skip_rgb_dit_load_from_pretrain: true
skip_action_dit_load_from_pretrain: true
checkpoint_init_only: true
depth_vae_require_latent_stats: true
depth_dit_checkpoint_path: null
depth_vae_checkpoint_path: depth_vae.pt
rgb_vae_checkpoint_path: rgb_vae.safetensors
action_dit_pretrained_path: null
depth_dit_config:
patch_size:
- 1
- 2
- 2
in_dim: 48
hidden_dim: 3072
ffn_dim: 14336
freq_dim: 256
text_dim: 4096
out_dim: 48
num_heads: 24
attn_head_dim: 128
num_layers: 30
eps: 1.0e-06
seperated_timestep: true
require_vae_embedding: false
fuse_vae_embedding_in_latents: true
use_gradient_checkpointing: true
video_attention_mask_mode: first_frame_causal
rgb_dit_config:
patch_size:
- 1
- 2
- 2
in_dim: 48
hidden_dim: 3072
ffn_dim: 14336
freq_dim: 256
text_dim: 4096
out_dim: 48
num_heads: 24
attn_head_dim: 128
num_layers: 30
eps: 1.0e-06
seperated_timestep: true
require_vae_embedding: false
fuse_vae_embedding_in_latents: true
use_gradient_checkpointing: true
video_attention_mask_mode: first_frame_causal
action_dit_config:
action_dim: 14
hidden_dim: 1024
ffn_dim: 4096
num_heads: 24
attn_head_dim: 128
num_layers: 30
text_dim: 4096
freq_dim: 256
eps: 1.0e-06
use_gradient_checkpointing: true
rgb_scheduler:
train_shift: 5.0
infer_shift: 5.0
num_train_timesteps: 1000
depth_scheduler:
train_shift: 5.0
infer_shift: 5.0
num_train_timesteps: 1000
action_scheduler:
train_shift: 5.0
infer_shift: 5.0
num_train_timesteps: 1000
loss:
lambda_rgb: 1.0
lambda_depth: 1.0
lambda_action: 1.0
depth_parent_expected_step: 15000
action_init_source: wan
lr_schedule_steps: 15000
data:
train:
video_size:
- 384
- 320
num_video_frames: 9
frame_stride: 4
rgb_history_num_frames: 5
rgb_history_frame_stride: 4
cameras:
- head_camera
- left_camera
- right_camera
layout: robotwin
depth_min: 0.0
depth_max: 1500.0
action_horizon: 32
action_dim: 14
action_start_offset: 1
proprio_start_offset: 0
context_len: 128
text_encoder_id: wan22ti2v5b
prompt_template: 'A video recorded from a robot''s point of view executing the
following instruction: {task}'
task_names: null
rgb_target_mode: f8
deployment:
action_horizon: 32
replan_steps: 24
num_inference_steps: 10
inference_shifts:
depth: 5.0
action: 5.0
benchmark: robotwin
portable_bundle: true
statistics_path: action_stats.pt