Merge remote-tracking branch 'upstream/main' into user/alexander-soare/multistep_policy_and_serial_env

lerobot/common/datasets/abstract.py

@@ -19,6 +19,7 @@ class AbstractExperienceReplay(TensorDictReplayBuffer):
     def __init__(
         self,
         dataset_id: str,
+        version: str | None = None,
         batch_size: int = None,
         *,
         shuffle: bool = True,
@@ -31,8 +32,15 @@ class AbstractExperienceReplay(TensorDictReplayBuffer):
         transform: "torchrl.envs.Transform" = None,
     ):
         self.dataset_id = dataset_id
+        self.version = version
         self.shuffle = shuffle
         self.root = root
+
+        if self.root is not None and self.version is not None:
+            logging.warning(
+                f"The version of the dataset ({self.version}) is not enforced when root is provided ({self.root})."
+            )
+
         storage = self._download_or_load_dataset()
 
         super().__init__(
@@ -96,10 +104,14 @@ class AbstractExperienceReplay(TensorDictReplayBuffer):
 
     def _download_or_load_dataset(self) -> torch.StorageBase:
         if self.root is None:
-            self.data_dir = Path(snapshot_download(repo_id=f"cadene/{self.dataset_id}", repo_type="dataset"))
+            self.data_dir = Path(
+                snapshot_download(
+                    repo_id=f"cadene/{self.dataset_id}", repo_type="dataset", revision=self.version
+                )
+            )
         else:
             self.data_dir = self.root / self.dataset_id
-        return TensorStorage(TensorDict.load_memmap(self.data_dir))
+        return TensorStorage(TensorDict.load_memmap(self.data_dir / "replay_buffer"))
 
     def _compute_stats(self, num_batch=100, batch_size=32):
         rb = TensorDictReplayBuffer(