Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by: Alexander Soare <alexander.soare159@gmail.com> Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com> Co-authored-by: Cadene <re.cadene@gmail.com>
43 lines
1.0 KiB
YAML
43 lines
1.0 KiB
YAML
defaults:
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- _self_
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- env: pusht
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- policy: diffusion
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hydra:
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run:
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dir: outputs/train/${now:%Y-%m-%d}/${now:%H-%M-%S}_${env.name}_${policy.name}_${hydra.job.name}
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job:
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name: default
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device: cuda # cpu
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# `seed` is used for training (eg: model initialization, dataset shuffling)
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# AND for the evaluation environments.
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seed: ???
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dataset_repo_id: lerobot/pusht
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training:
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offline_steps: ???
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online_steps: ???
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online_steps_between_rollouts: ???
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online_sampling_ratio: 0.5
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# `online_env_seed` is used for environments for online training data rollouts.
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online_env_seed: ???
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eval_freq: ???
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save_freq: ???
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log_freq: 250
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save_model: true
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eval:
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n_episodes: 1
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# `batch_size` specifies the number of environments to use in a gym.vector.VectorEnv.
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batch_size: 1
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# `use_async_envs` specifies whether to use asynchronous environments (multiprocessing).
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use_async_envs: false
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wandb:
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enable: true
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# Set to true to disable saving an artifact despite save_model == True
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disable_artifact: false
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project: lerobot
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notes: ""
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