Batch normalization.

tf.compat.v2.nn.batch_norm_with_global_normalization( input, mean, variance, beta, gamma, variance_epsilon, scale_after_normalization, name=None )

This op is deprecated. See `tf.nn.batch_normalization`

.

Args | |
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`input` | A 4D input Tensor. |

`mean` | A 1D mean Tensor with size matching the last dimension of t. This is the first output from tf.nn.moments, or a saved moving average thereof. |

`variance` | A 1D variance Tensor with size matching the last dimension of t. This is the second output from tf.nn.moments, or a saved moving average thereof. |

`beta` | A 1D beta Tensor with size matching the last dimension of t. An offset to be added to the normalized tensor. |

`gamma` | A 1D gamma Tensor with size matching the last dimension of t. If "scale_after_normalization" is true, this tensor will be multiplied with the normalized tensor. |

`variance_epsilon` | A small float number to avoid dividing by 0. |

`scale_after_normalization` | A bool indicating whether the resulted tensor needs to be multiplied with gamma. |

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

Returns | |
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A batch-normalized `t` . |

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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/r1.15/api_docs/python/tf/compat/v2/nn/batch_norm_with_global_normalization