def __iter__()

in src/azstoragetorch/datasets.py [0:0]

• 5 lines of code
• 3 McCabe index (conditional complexity)

    def __iter__(self) -> Iterator[_TransformOutputType_co]:
        """Iterate over the blobs in the dataset.

        :returns: An iterator over the blobs, with ``transform`` applied, in the dataset.
            The ``transform`` is applied lazily to each blob as it is yielded.
        """
        worker_info = torch.utils.data.get_worker_info()
        for i, blob in enumerate(self._blobs):
            if self._should_yield_from_worker_shard(worker_info, i):
                yield self._transform(blob)