| resume: false | |
| device: cuda | |
| use_amp: true | |
| seed: 100000 | |
| dataset_repo_id: lerobot/pusht_keypoints | |
| video_backend: pyav | |
| training: | |
| offline_steps: 1000000 | |
| num_workers: 24 | |
| batch_size: 24 | |
| eval_freq: 10000 | |
| log_freq: 1000 | |
| save_checkpoint: true | |
| save_freq: 50000 | |
| 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 | |
| save_model: true | |
| grad_clip_norm: 50 | |
| lr: 0.0001 | |
| min_lr: 0.0001 | |
| lr_cycle_steps: 300000 | |
| weight_decay: 1.0e-05 | |
| delta_timestamps: | |
| observation.environment_state: | |
| - -1.5 | |
| - -1.4 | |
| - -1.3 | |
| - -1.2 | |
| - -1.1 | |
| - -1.0 | |
| - -0.9 | |
| - -0.8 | |
| - -0.7 | |
| - -0.6 | |
| - -0.5 | |
| - -0.1 | |
| - 0.0 | |
| observation.state: | |
| - -1.5 | |
| - -1.4 | |
| - -1.3 | |
| - -1.2 | |
| - -1.1 | |
| - -1.0 | |
| - -0.9 | |
| - -0.8 | |
| - -0.7 | |
| - -0.6 | |
| - -0.5 | |
| - -0.1 | |
| - 0.0 | |
| action: | |
| - -1.5 | |
| - -1.4 | |
| - -1.3 | |
| - -1.2 | |
| - -1.1 | |
| - -1.0 | |
| - -0.9 | |
| - -0.8 | |
| - -0.7 | |
| - -0.6 | |
| - -0.5 | |
| - -0.1 | |
| - 0.0 | |
| - 0.1 | |
| - 0.2 | |
| - 0.3 | |
| - 0.4 | |
| - 0.5 | |
| - 0.6 | |
| - 0.7 | |
| - 0.8 | |
| - 0.9 | |
| - 1.0 | |
| - 1.1 | |
| - 1.2 | |
| - 1.3 | |
| - 1.4 | |
| - 1.5 | |
| - 1.6 | |
| - 1.7 | |
| - 1.8 | |
| - 1.9 | |
| - 2.0 | |
| - 2.1 | |
| - 2.2 | |
| - 2.3 | |
| - 2.4 | |
| - 2.5 | |
| - 2.6 | |
| - 2.7 | |
| - 2.8 | |
| - 2.9 | |
| eval: | |
| n_episodes: 100 | |
| batch_size: 100 | |
| use_async_envs: false | |
| wandb: | |
| enable: true | |
| disable_artifact: false | |
| project: pusht | |
| notes: '' | |
| fps: 10 | |
| env: | |
| name: pusht | |
| task: PushT-v0 | |
| image_size: 96 | |
| state_dim: 2 | |
| action_dim: 2 | |
| fps: ${fps} | |
| episode_length: 300 | |
| gym: | |
| obs_type: environment_state_agent_pos | |
| render_mode: rgb_array | |
| visualization_width: 384 | |
| visualization_height: 384 | |
| override_dataset_stats: | |
| observation.environment_state: | |
| min: | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| - 0.0 | |
| max: | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| - 512.0 | |
| observation.state: | |
| min: | |
| - 0.0 | |
| - 0.0 | |
| max: | |
| - 512.0 | |
| - 512.0 | |
| action: | |
| min: | |
| - 0.0 | |
| - 0.0 | |
| max: | |
| - 512.0 | |
| - 512.0 | |
| policy: | |
| name: dot | |
| n_obs_steps: 3 | |
| train_horizon: 30 | |
| inference_horizon: 30 | |
| lookback_obs_steps: 10 | |
| lookback_aug: 5 | |
| input_shapes: | |
| observation.environment_state: | |
| - 16 | |
| observation.state: | |
| - ${env.state_dim} | |
| output_shapes: | |
| action: | |
| - ${env.action_dim} | |
| input_normalization_modes: | |
| observation.environment_state: min_max | |
| observation.state: min_max | |
| output_normalization_modes: | |
| action: min_max | |
| state_noise: 0.01 | |
| noise_decay: 0.999995 | |
| pre_norm: true | |
| dim_model: 128 | |
| n_heads: 8 | |
| dim_feedforward: 512 | |
| n_decoder_layers: 8 | |
| dropout: 0.1 | |
| alpha: 0.75 | |
| train_alpha: 0.9 | |
| predict_every_n: 1 | |
| return_every_n: 2 | |