| resume: false |
| device: cuda |
| use_amp: false |
| seed: 1000 |
| dataset_repo_id: jmercat/koch_feed_cat |
| video_backend: pyav |
| training: |
| offline_steps: 8000 |
| num_workers: 4 |
| batch_size: 64 |
| eval_freq: -1 |
| log_freq: 200 |
| save_checkpoint: true |
| save_freq: 800 |
| online_steps: 0 |
| online_rollout_n_episodes: 1 |
| online_rollout_batch_size: 1 |
| online_steps_between_rollouts: 1 |
| online_sampling_ratio: 0.5 |
| online_env_seed: null |
| online_buffer_capacity: null |
| online_buffer_seed_size: 0 |
| do_online_rollout_async: false |
| image_transforms: |
| enable: false |
| max_num_transforms: 3 |
| random_order: false |
| brightness: |
| weight: 1 |
| min_max: |
| - 0.8 |
| - 1.2 |
| contrast: |
| weight: 1 |
| min_max: |
| - 0.8 |
| - 1.2 |
| saturation: |
| weight: 1 |
| min_max: |
| - 0.5 |
| - 1.5 |
| hue: |
| weight: 1 |
| min_max: |
| - -0.05 |
| - 0.05 |
| sharpness: |
| weight: 1 |
| min_max: |
| - 0.8 |
| - 1.2 |
| grad_clip_norm: 10 |
| lr: 0.0001 |
| lr_scheduler: cosine |
| lr_warmup_steps: 500 |
| adam_betas: |
| - 0.95 |
| - 0.999 |
| adam_eps: 1.0e-08 |
| adam_weight_decay: 1.0e-06 |
| delta_timestamps: |
| action: |
| - 0.0 |
| - 0.03333333333333333 |
| - 0.06666666666666667 |
| - 0.1 |
| - 0.13333333333333333 |
| - 0.16666666666666666 |
| - 0.2 |
| - 0.23333333333333334 |
| - 0.26666666666666666 |
| - 0.3 |
| - 0.3333333333333333 |
| - 0.36666666666666664 |
| - 0.4 |
| - 0.43333333333333335 |
| - 0.4666666666666667 |
| - 0.5 |
| eval: |
| n_episodes: 5 |
| batch_size: 5 |
| use_async_envs: false |
| wandb: |
| enable: true |
| disable_artifact: false |
| project: lerobot |
| notes: '' |
| fps: 30 |
| env: |
| name: real_world |
| task: null |
| state_dim: 6 |
| action_dim: 6 |
| fps: ${fps} |
| policy: |
| name: diffusion |
| n_obs_steps: 1 |
| horizon: 16 |
| n_action_steps: 8 |
| input_shapes: |
| observation.images.phone: |
| - 3 |
| - 480 |
| - 640 |
| observation.state: |
| - ${env.state_dim} |
| output_shapes: |
| action: |
| - ${env.action_dim} |
| input_normalization_modes: |
| observation.images.phone: mean_std |
| observation.state: mean_std |
| output_normalization_modes: |
| action: mean_std |
| vision_backbone: resnet18 |
| crop_shape: |
| - 432 |
| - 576 |
| crop_is_random: true |
| pretrained_backbone_weights: ResNet18_Weights.IMAGENET1K_V1 |
| use_group_norm: false |
| spatial_softmax_num_keypoints: 32 |
| down_dims: |
| - 512 |
| - 1024 |
| - 2048 |
| kernel_size: 5 |
| n_groups: 8 |
| diffusion_step_embed_dim: 128 |
| use_film_scale_modulation: true |
| noise_scheduler_type: DDPM |
| num_train_timesteps: 100 |
| beta_schedule: squaredcos_cap_v2 |
| beta_start: 0.0001 |
| beta_end: 0.02 |
| prediction_type: epsilon |
| clip_sample: true |
| clip_sample_range: 1.0 |
| num_inference_steps: null |
| do_mask_loss_for_padding: false |
|
|
