tf.raw_ops.ShuffleDataset

Creates a dataset that shuffles elements from input_dataset pseudorandomly.

tf.raw_ops.ShuffleDataset(
    input_dataset,
    buffer_size,
    seed,
    seed2,
    output_types,
    output_shapes,
    reshuffle_each_iteration=True,
    metadata='',
    name=None
)

input_dataset A Tensor of type variant.
buffer_size A Tensor of type int64. The number of output elements to buffer in an iterator over this dataset. Compare with the min_after_dequeue attr when creating a RandomShuffleQueue.
seed A Tensor of type int64. A scalar seed for the random number generator. If either seed or seed2 is set to be non-zero, the random number generator is seeded by the given seed. Otherwise, a random seed is used.
seed2 A Tensor of type int64. A second scalar seed to avoid seed collision.
output_types A list of tf.DTypes that has length >= 1.
output_shapes A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1.
reshuffle_each_iteration An optional bool. Defaults to True. If true, each iterator over this dataset will be given a different pseudorandomly generated seed, based on a sequence seeded by the seed and seed2 inputs. If false, each iterator will be given the same seed, and repeated iteration over this dataset will yield the exact same sequence of results.
metadata An optional string. Defaults to "".
name A name for the operation (optional).

A Tensor of type variant.