tensorflow::ops::QuantizedBatchNormWithGlobalNormalization

#include <nn_ops.h>

Quantized Batch normalization.

Summary

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

Args:

scope: A Scope object
t: A 4D input Tensor.
t_min: The value represented by the lowest quantized input.
t_max: The value represented by the highest quantized input.
m: 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: The value represented by the lowest quantized mean.
m_max: The value represented by the highest quantized mean.
v: 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: The value represented by the lowest quantized variance.
v_max: The value represented by the highest quantized variance.
beta: A 1D beta Tensor with size matching the last dimension of t. An offset to be added to the normalized tensor.
beta_min: The value represented by the lowest quantized offset.
beta_max: The value represented by the highest quantized offset.
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.
gamma_min: The value represented by the lowest quantized gamma.
gamma_max: The value represented by the highest quantized gamma.
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.

Returns:

Output result
Output result_min
Output result_max

Constructors and Destructors
QuantizedBatchNormWithGlobalNormalization(const ::tensorflow::Scope & scope, ::tensorflow::Input t, ::tensorflow::Input t_min, ::tensorflow::Input t_max, ::tensorflow::Input m, ::tensorflow::Input m_min, ::tensorflow::Input m_max, ::tensorflow::Input v, ::tensorflow::Input v_min, ::tensorflow::Input v_max, ::tensorflow::Input beta, ::tensorflow::Input beta_min, ::tensorflow::Input beta_max, ::tensorflow::Input gamma, ::tensorflow::Input gamma_min, ::tensorflow::Input gamma_max, DataType out_type, float variance_epsilon, bool scale_after_normalization)

Constructors and Destructors

QuantizedBatchNormWithGlobalNormalization(const ::tensorflow::Scope & scope, ::tensorflow::Input t, ::tensorflow::Input t_min, ::tensorflow::Input t_max, ::tensorflow::Input m, ::tensorflow::Input m_min, ::tensorflow::Input m_max, ::tensorflow::Input v, ::tensorflow::Input v_min, ::tensorflow::Input v_max, ::tensorflow::Input beta, ::tensorflow::Input beta_min, ::tensorflow::Input beta_max, ::tensorflow::Input gamma, ::tensorflow::Input gamma_min, ::tensorflow::Input gamma_max, DataType out_type, float variance_epsilon, bool scale_after_normalization)

Public attributes
`operation`	`Operation`
`result`	`::tensorflow::Output`
`result_max`	`::tensorflow::Output`
`result_min`	`::tensorflow::Output`

Public attributes

operation

Operation operation

result

::tensorflow::Output result

result_max

::tensorflow::Output result_max

result_min

::tensorflow::Output result_min

Public functions

QuantizedBatchNormWithGlobalNormalization

 QuantizedBatchNormWithGlobalNormalization(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input t,
  ::tensorflow::Input t_min,
  ::tensorflow::Input t_max,
  ::tensorflow::Input m,
  ::tensorflow::Input m_min,
  ::tensorflow::Input m_max,
  ::tensorflow::Input v,
  ::tensorflow::Input v_min,
  ::tensorflow::Input v_max,
  ::tensorflow::Input beta,
  ::tensorflow::Input beta_min,
  ::tensorflow::Input beta_max,
  ::tensorflow::Input gamma,
  ::tensorflow::Input gamma_min,
  ::tensorflow::Input gamma_max,
  DataType out_type,
  float variance_epsilon,
  bool scale_after_normalization
)