add TODO
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@ -152,7 +152,13 @@ class AbstractDataset(TensorDictReplayBuffer):
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return TensorStorage(TensorDict.load_memmap(self.data_dir / "replay_buffer"))
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return TensorStorage(TensorDict.load_memmap(self.data_dir / "replay_buffer"))
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def _compute_stats(self, batch_size: int = 32):
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def _compute_stats(self, batch_size: int = 32):
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"""Compute dataset statistics including minimum, maximum, mean, and standard deviation."""
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"""Compute dataset statistics including minimum, maximum, mean, and standard deviation.
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TODO(alexander-soare): Add a num_batches argument which essentially allows one to use a subset of the
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full dataset (for handling very large datasets). The sampling would then have to be random
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(preferably without replacement). Both stats computation loops would ideally sample the same
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items.
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"""
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rb = TensorDictReplayBuffer(
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rb = TensorDictReplayBuffer(
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storage=self._storage,
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storage=self._storage,
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batch_size=32,
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batch_size=32,
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