fix(dataset_tools) Critical bug in modify features (#2342)

* fix bug in `_copy_data_with_feature_changes`

* Update src/lerobot/datasets/dataset_tools.py

Co-authored-by: Caroline Pascal <caroline8.pascal@gmail.com>
Signed-off-by: Michel Aractingi <michel.aractingi@huggingface.co>

* add missing import

---------

Signed-off-by: Michel Aractingi <michel.aractingi@huggingface.co>
Co-authored-by: Caroline Pascal <caroline8.pascal@gmail.com>

src/lerobot/datasets/dataset_tools.py

@@ -39,6 +39,7 @@ from lerobot.datasets.aggregate import aggregate_datasets
 from lerobot.datasets.compute_stats import aggregate_stats
 from lerobot.datasets.lerobot_dataset import LeRobotDataset, LeRobotDatasetMetadata
 from lerobot.datasets.utils import (
+    DATA_DIR,
     DEFAULT_CHUNK_SIZE,
     DEFAULT_DATA_FILE_SIZE_IN_MB,
     DEFAULT_DATA_PATH,
@@ -962,28 +963,23 @@ def _copy_data_with_feature_changes(
     remove_features: list[str] | None = None,
 ) -> None:
     """Copy data while adding or removing features."""
-    if dataset.meta.episodes is None:
+    data_dir = dataset.root / DATA_DIR
-        dataset.meta.episodes = load_episodes(dataset.meta.root)
+    parquet_files = sorted(data_dir.glob("*/*.parquet"))
 
-    # Map file paths to episode indices to extract chunk/file indices
+    if not parquet_files:
-    file_to_episodes: dict[Path, set[int]] = {}
+        raise ValueError(f"No parquet files found in {data_dir}")
-    for ep_idx in range(dataset.meta.total_episodes):
-        file_path = dataset.meta.get_data_file_path(ep_idx)
-        if file_path not in file_to_episodes:
-            file_to_episodes[file_path] = set()
-        file_to_episodes[file_path].add(ep_idx)
 
     frame_idx = 0
 
-    for src_path in tqdm(sorted(file_to_episodes.keys()), desc="Processing data files"):
+    for src_path in tqdm(parquet_files, desc="Processing data files"):
-        df = pd.read_parquet(dataset.root / src_path).reset_index(drop=True)
+        df = pd.read_parquet(src_path).reset_index(drop=True)
 
-        # Get chunk_idx and file_idx from the source file's first episode
+        relative_path = src_path.relative_to(dataset.root)
-        episodes_in_file = file_to_episodes[src_path]
+        chunk_dir = relative_path.parts[1]
-        first_ep_idx = min(episodes_in_file)
+        file_name = relative_path.parts[2]
-        src_ep = dataset.meta.episodes[first_ep_idx]
+
-        chunk_idx = src_ep["data/chunk_index"]
+        chunk_idx = int(chunk_dir.split("-")[1])
-        file_idx = src_ep["data/file_index"]
+        file_idx = int(file_name.split("-")[1].split(".")[0])
 
         if remove_features:
             df = df.drop(columns=remove_features, errors="ignore")
@@ -1009,7 +1005,7 @@ def _copy_data_with_feature_changes(
                         df[feature_name] = feature_slice
             frame_idx = end_idx
 
-        # Write using the preserved chunk_idx and file_idx from source
+        # Write using the same chunk/file structure as source
         dst_path = new_meta.root / DEFAULT_DATA_PATH.format(chunk_index=chunk_idx, file_index=file_idx)
         dst_path.parent.mkdir(parents=True, exist_ok=True)