From f5bf6bb028f2476f2f1ec85633d67e8e22eff51e Mon Sep 17 00:00:00 2001 From: nemo Date: Fri, 5 Dec 2025 12:48:07 +0100 Subject: [PATCH] Make it possible to unset policy features This is necessary to train pre-trained policies on new datasets so that the features are inferred from the new dataset and not from the pretrained policy. --- src/lerobot/configs/policies.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/lerobot/configs/policies.py b/src/lerobot/configs/policies.py index df1559ac2..cc97142a3 100644 --- a/src/lerobot/configs/policies.py +++ b/src/lerobot/configs/policies.py @@ -55,8 +55,9 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC): # type: igno n_obs_steps: int = 1 - input_features: dict[str, PolicyFeature] = field(default_factory=dict) - output_features: dict[str, PolicyFeature] = field(default_factory=dict) + # `input_features` can be set to None/null in order to infer those values from the dataset. + input_features: dict[str, PolicyFeature] | None = field(default_factory=dict) + output_features: dict[str, PolicyFeature] | None = field(default_factory=dict) device: str | None = None # e.g. "cuda", "cuda:0", "cpu", or "mps" # `use_amp` determines whether to use Automatic Mixed Precision (AMP) for training and evaluation. With AMP,