Quantized Batch normalization.

tf.raw_ops.QuantizedBatchNormWithGlobalNormalization( t, t_min, t_max, m, m_min, m_max, v, v_min, v_max, beta, beta_min, beta_max, gamma, gamma_min, gamma_max, out_type, variance_epsilon, scale_after_normalization, name=None )

This op is deprecated and will be removed in the future. Prefer `tf.nn.batch_normalization`

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Args | |
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`t` | A `Tensor` . Must be one of the following types: `qint8` , `quint8` , `qint32` , `qint16` , `quint16` . A 4D input Tensor. |

`t_min` | A `Tensor` of type `float32` . The value represented by the lowest quantized input. |

`t_max` | A `Tensor` of type `float32` . The value represented by the highest quantized input. |

`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. |

`m_min` | A `Tensor` of type `float32` . The value represented by the lowest quantized mean. |

`m_max` | A `Tensor` of type `float32` . The value represented by the highest quantized mean. |

`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. |

`v_min` | A `Tensor` of type `float32` . The value represented by the lowest quantized variance. |

`v_max` | A `Tensor` of type `float32` . The value represented by the highest quantized variance. |

`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. |

`beta_min` | A `Tensor` of type `float32` . The value represented by the lowest quantized offset. |

`beta_max` | A `Tensor` of type `float32` . The value represented by the highest quantized offset. |

`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. |

`gamma_min` | A `Tensor` of type `float32` . The value represented by the lowest quantized gamma. |

`gamma_max` | A `Tensor` of type `float32` . The value represented by the highest quantized gamma. |

`out_type` | A `tf.DType` from: `tf.qint8, tf.quint8, tf.qint32, tf.qint16, tf.quint16` . |

`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 tuple of `Tensor` objects (result, result_min, result_max). | |

`result` | A `Tensor` of type `out_type` . |

`result_min` | A `Tensor` of type `float32` . |

`result_max` | A `Tensor` of type `float32` . |

© 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/raw_ops/QuantizedBatchNormWithGlobalNormalization