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, name=None )

Args | |
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`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. |

`name` | A name for the operation (optional). |

Returns | |
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A `Tensor` of type `variant` . |

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/ShuffleDataset