class StepExamplesIterable(_BaseExamplesIterable):
    def __init__(self, ex_iterable: _BaseExamplesIterable, step: int, offset: int):
        super().__init__()
        self.ex_iterable = ex_iterable
        self.step = step
        self.offset = offset
        # TODO(QL): implement iter_arrow

    @property
    def is_typed(self):
        return self.ex_iterable.is_typed

    @property
    def features(self):
        return self.ex_iterable.features

    def _init_state_dict(self) -> dict:
        self._state_dict = self.ex_iterable._init_state_dict()
        return self._state_dict

    def __iter__(self):
        ex_iterator = iter(self.ex_iterable)
        while True:
            batch = list(islice(ex_iterator, self.step))
            if len(batch) > self.offset:
                yield batch[self.offset]
            else:
                break

    def shuffle_data_sources(self, generator: np.random.Generator) -> "StepExamplesIterable":
        return StepExamplesIterable(
            self.ex_iterable.shuffle_data_sources(generator), step=self.step, offset=self.offset
        )

    def shard_data_sources(self, num_shards: int, index: int, contiguous=True) -> "StepExamplesIterable":
        return StepExamplesIterable(
            self.ex_iterable.shard_data_sources(num_shards, index, contiguous=contiguous),
            step=self.step,
            offset=self.offset,
        )

    @property
    def num_shards(self) -> int:
        return self.ex_iterable.num_shards
/Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/iterable_dataset.py