resume: false device: cuda use_amp: true seed: 100000 dataset_repo_id: alexandersoare/pusht_keypoints_only video_backend: pyav training: offline_steps: 200000 online_steps: 0 online_steps_between_rollouts: 1 online_sampling_ratio: 0.5 online_env_seed: ??? eval_freq: 10000 log_freq: 50 save_checkpoint: true save_freq: 20000 num_workers: 4 batch_size: 64 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: observation.environment_state: - -0.1 - 0.0 observation.state: - -0.1 - 0.0 action: - -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 drop_n_last_frames: 7 eval: n_episodes: 50 batch_size: 50 use_async_envs: false wandb: enable: true disable_artifact: true project: lerobot 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 policy: name: diffusion n_obs_steps: 2 horizon: 16 n_action_steps: 8 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 vision_backbone: resnet18 crop_shape: - 84 - 84 crop_is_random: true pretrained_backbone_weights: null use_group_norm: true 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: DDIM 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: 10 do_mask_loss_for_padding: false