tf.raw_ops.ShuffleAndRepeatDataset

Creates a dataset that shuffles and repeats elements from input_dataset

tf.raw_ops.ShuffleAndRepeatDataset(
    input_dataset, buffer_size, seed, seed2, count, output_types, output_shapes,
    name=None
)

pseudorandomly.

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.
count A Tensor of type int64. A scalar representing the number of times the underlying dataset should be repeated. The default is -1, which results in infinite repetition.
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.
name A name for the operation (optional).

A Tensor of type variant.