backup wip

lerobot/common/policies/act/configuration_act.py

@@ -56,7 +56,7 @@ class ActionChunkingTransformerConfig:
 
     # Inputs / output structure.
     n_obs_steps: int = 1
-    camera_names: list[str] = field(default_factory=lambda: ["top"])
+    camera_names: tuple[str] = ("top",)
     chunk_size: int = 100
     n_action_steps: int = 100
 
@@ -101,7 +101,7 @@ class ActionChunkingTransformerConfig:
     utd: int = 1
 
     def __post_init__(self):
-        """Input validation."""
+        """Input validation (not exhaustive)."""
         if not self.vision_backbone.startswith("resnet"):
             raise ValueError("`vision_backbone` must be one of the ResNet variants.")
         if self.use_temporal_aggregation:

lerobot/common/policies/act/modeling_act.py

@@ -163,7 +163,8 @@ class ActionChunkingTransformerPolicy(nn.Module):
 
     @torch.no_grad
     def select_action(self, batch: dict[str, Tensor], **_) -> Tensor:
-        """
+        """Select a single action given environment observations.
+
         This method wraps `select_actions` in order to return one action at a time for execution in the
         environment. It works by managing the actions in a queue and only calling `select_actions` when the
         queue is empty.