How to use the tfrecord.iterator_utils.shuffle_iterator function in tfrecord

To help you get started, we’ve selected a few tfrecord examples, based on popular ways it is used in public projects.

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github vahidk / tfrecord / tfrecord / torch / View on Github external
def __iter__(self):
        worker_info =
        if worker_info is not None:
            np.random.seed(worker_info.seed % np.iinfo(np.uint32).max)
        it = reader.multi_tfrecord_loader(
            self.data_pattern, self.index_pattern, self.splits, self.description)
        if self.shuffle_queue_size:
            it = iterator_utils.shuffle_iterator(it, self.shuffle_queue_size)
        if self.transform:
            it = map(self.transform, it)
        return it