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Outputs deterministic pseudorandom values from a normal distribution.

tf.random.stateless_normal( shape, seed, mean=0.0, stddev=1.0, dtype=tf.dtypes.float32, name=None )

This is a stateless version of `tf.random.normal`

: if run twice with the same seeds and shapes, it will produce the same pseudorandom numbers. The output is consistent across multiple runs on the same hardware (and between CPU and GPU), but may change between versions of TensorFlow or on non-CPU/GPU hardware.

Args | |
---|---|

`shape` | A 1-D integer Tensor or Python array. The shape of the output tensor. |

`seed` | A shape [2] Tensor, the seed to the random number generator. Must have dtype `int32` or `int64` . (When using XLA, only `int32` is allowed.) |

`mean` | A 0-D Tensor or Python value of type `dtype` . The mean of the normal distribution. |

`stddev` | A 0-D Tensor or Python value of type `dtype` . The standard deviation of the normal distribution. |

`dtype` | The type of the output. |

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

Returns | |
---|---|

A tensor of the specified shape filled with random normal values. |

© 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/r2.4/api_docs/python/tf/random/stateless_normal