| resume: false | |
| device: cuda | |
| use_amp: false | |
| seed: 1000 | |
| dataset_repo_id: jmercat/koch_feed_cat_2 | |
| video_backend: pyav | |
| training: | |
| offline_steps: 16000 | |
| num_workers: 4 | |
| batch_size: 64 | |
| eval_freq: -1 | |
| log_freq: 200 | |
| save_checkpoint: true | |
| save_freq: 1600 | |
| 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 | |
| - 512 | |
| - 512 | |
| 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: sample | |
| clip_sample: true | |
| clip_sample_range: 1.0 | |
| num_inference_steps: null | |
| do_mask_loss_for_padding: false | |