Batch normalization.

tf.raw_ops.BatchNormWithGlobalNormalization( t, m, v, beta, gamma, variance_epsilon, scale_after_normalization, name=None )

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

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Args | |
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`t` | A `Tensor` . Must be one of the following types: `float32` , `float64` , `int32` , `uint8` , `int16` , `int8` , `complex64` , `int64` , `qint8` , `quint8` , `qint32` , `bfloat16` , `uint16` , `complex128` , `half` , `uint32` , `uint64` . A 4D input Tensor. |

`m` | A `Tensor` . Must have the same type as `t` . 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. |

`v` | A `Tensor` . Must have the same type as `t` . 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 `Tensor` . Must have the same type as `t` . A 1D beta Tensor with size matching the last dimension of t. An offset to be added to the normalized tensor. |

`gamma` | A `Tensor` . Must have the same type as `t` . 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 `float` . A small float number to avoid dividing by 0. |

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

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

Returns | |
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A `Tensor` . Has the same type as `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/r2.4/api_docs/python/tf/raw_ops/BatchNormWithGlobalNormalization