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,
reshuffle_each_iteration=True,
metadata='',
name=None
)
pseudorandomly.
Args | |
---|---|
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 .
|
reshuffle_each_iteration
|
An optional bool . Defaults to True .
|
metadata
|
An optional string . Defaults to "" .
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A Tensor of type variant .
|