fix(datasets): remove unreachable timestamp branch in add_frame (#3163)

* fix(datasets): remove unreachable timestamp branch in add_frame and document caller contract

- Remove dead code: frame.pop("timestamp") branch in add_frame() could never
  execute because validate_frame() raises ValueError for any DEFAULT_FEATURES
  key (including timestamp) before we reach that line.
- Expand add_frame() docstring: explicitly document that timestamp and
  frame_index must NOT be passed by the caller.
- Add explanatory comment in validate_frame(): clarifies why DEFAULT_FEATURES
  are excluded from expected_features, preventing future re-introduction of
  the dead branch.

The dead branch originated in #1200, which fixed a shape-(1,) mismatch for a
code path that was subsequently made unreachable by a refactor of validate_frame.

* chore(datasets): narrow PR scope

* fix(datasets): move add_frame timestamp cleanup to dataset_writer

src/lerobot/datasets/dataset_writer.py

@@ -155,7 +155,16 @@ class DatasetWriter:
             self.image_writer.save_image(image=image, fpath=fpath, compress_level=compress_level)
 
     def add_frame(self, frame: dict) -> None:
-        """Add a frame to the episode_buffer. Images are written to a temporary directory."""
+        """
+        Add a single frame to the current episode buffer.
+
+        Apart from images written to a temporary directory, nothing is written to disk
+        until ``save_episode()`` is called.
+
+        The caller must provide all user-defined features plus ``"task"``, and must
+        not provide ``"timestamp"`` or ``"frame_index"``; those are computed
+        automatically.
+        """
         # Convert torch to numpy if needed
         for name in frame:
             if isinstance(frame[name], torch.Tensor):
@@ -168,7 +177,7 @@ class DatasetWriter:
 
         # Automatically add frame_index and timestamp to episode buffer
         frame_index = self.episode_buffer["size"]
-        timestamp = frame.pop("timestamp") if "timestamp" in frame else frame_index / self._meta.fps
+        timestamp = frame_index / self._meta.fps
         self.episode_buffer["frame_index"].append(frame_index)
         self.episode_buffer["timestamp"].append(timestamp)
         self.episode_buffer["task"].append(frame.pop("task"))

src/lerobot/datasets/feature_utils.py

@@ -365,6 +365,10 @@ def get_delta_indices(delta_timestamps: dict[str, list[float]], fps: int) -> dic
 
 
 def validate_frame(frame: dict, features: dict) -> None:
+    # DEFAULT_FEATURES (timestamp, frame_index, episode_index, index, task_index) are
+    # auto-populated by the recording pipeline (add_frame / save_episode) and must not
+    # be supplied by the caller. Excluding them here means any frame dict that contains
+    # these keys will be rejected as extra features.
     expected_features = set(features) - set(DEFAULT_FEATURES)
     actual_features = set(frame)