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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