mbrl/util/replay_buffer.py [263:282]:
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            rng=rng,
        )
        self.transitions = transitions

    @staticmethod
    def _get_indices_valid_starts(
        trajectory_indices: List[Tuple[int, int]],
        sequence_length: int,
    ) -> np.ndarray:
        # This is memory and time inefficient but it's only done once when creating the
        # iterator. It's a good price to pay for now, since it simplifies things
        # enormously and it's less error prone
        valid_starts = []
        for (start, end) in trajectory_indices:
            if end - start < sequence_length:
                continue
            valid_starts.extend(list(range(start, end - sequence_length + 1)))
        return np.array(valid_starts)

    def __iter__(self):
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mbrl/util/replay_buffer.py [358:377]:
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            rng=rng,
        )
        self.transitions = transitions

    @staticmethod
    def _get_indices_valid_starts(
        trajectory_indices: List[Tuple[int, int]],
        sequence_length: int,
    ) -> np.ndarray:
        # This is memory and time inefficient but it's only done once when creating the
        # iterator. It's a good price to pay for now, since it simplifies things
        # enormously and it's less error prone
        valid_starts = []
        for (start, end) in trajectory_indices:
            if end - start < sequence_length:
                continue
            valid_starts.extend(list(range(start, end - sequence_length + 1)))
        return np.array(valid_starts)

    def __iter__(self):
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