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,
reshuffle_each_iteration=True, 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. |
name |
A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor of type variant. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/ShuffleAndRepeatDataset