refactor(datasets): resolve episode indices consistently

Make LeRobotDataset own episode selection policy: resolve the allowlist
via resolve_episode_indices (replacing the old warn-only out-of-range
handling, which now raises on an empty selection) and apply episode_filter,
then hand the finalized set to DatasetReader. The reader no longer
re-resolves, removing the duplicate resolution, and computes num_frames
from episode metadata so it stays consistent with the streaming path.

src/lerobot/datasets/dataset_reader.py

@@ -39,7 +39,6 @@ from .io_utils import (
     hf_transform_to_torch,
     load_nested_dataset,
 )
-from .utils import resolve_episode_indices
 from .video_utils import decode_video_frames
 
 
@@ -69,8 +68,9 @@ class DatasetReader:
         Args:
             meta: Dataset metadata instance.
             root: Local dataset root directory.
-            episodes: Optional list of episode indices to select. ``None``
-                means all episodes.
+            episodes: Optional list of episode indices to select, assumed
+                already validated by the caller. ``None`` means
+                all episodes.
             tolerance_s: Timestamp synchronization tolerance in seconds.
             video_backend: Video decoding backend identifier.
             delta_timestamps: Optional dict mapping feature keys to lists of
@@ -84,7 +84,7 @@ class DatasetReader:
         """
         self._meta = meta
         self.root = root
-        self.episodes = resolve_episode_indices(episodes, meta.total_episodes)
+        self.episodes = episodes
         self._tolerance_s = tolerance_s
         self._video_backend = video_backend
         if image_transforms is not None and not callable(image_transforms):
@@ -152,9 +152,9 @@ class DatasetReader:
     @property
     def num_frames(self) -> int:
         """Number of frames in selected episodes."""
-        if self.episodes is not None and self.hf_dataset is not None:
-            return len(self.hf_dataset)
-        return self._meta.total_frames
+        if self.episodes is None:
+            return self._meta.total_frames
+        return sum(self._meta.episodes[ep]["length"] for ep in self.episodes)
 
     @property
     def num_episodes(self) -> int:

src/lerobot/datasets/lerobot_dataset.py

@@ -34,6 +34,7 @@ from .utils import (
     create_lerobot_dataset_card,
     get_safe_version,
     is_valid_version,
+    resolve_episode_indices,
 )
 from .video_utils import (
     StreamingVideoEncoder,
@@ -237,13 +238,14 @@ class LeRobotDataset(torch.utils.data.Dataset):
         self.revision = self.meta.revision
         self.meta.rescale_depth_stats(self._depth_output_unit)
 
-        if episodes is not None and any(
-            episode >= self.meta.total_episodes or episode < 0 for episode in episodes
-        ):
-            logger.warning(
-                f"Some episodes in the provided episodes list are out of range for this dataset ({self.meta.total_episodes})."
+        # Selection policy (allowlist resolution + predicate filter) is owned here;
+        # the reader just consumes the finalized episode index set.
+        episodes = resolve_episode_indices(episodes, self.meta.total_episodes)
+        if episodes is not None and not episodes:
+            raise ValueError(
+                "No valid episodes: the requested episode selection is empty after resolving "
+                f"against the dataset range [0, {self.meta.total_episodes})."
             )
-
         if episode_filter is not None:
             resolved = self.meta.filter_episodes(episode_filter, candidates=episodes)
             if not resolved: