tensorflow::ops::QuantizedReluX

tensorflow::ops::QuantizedReluX

#include <nn_ops.h>

Computes Quantized Rectified Linear X: min(max(features, 0), max_value)

Summary

Arguments:

  • scope: A Scope object
  • min_features: The float value that the lowest quantized value represents.
  • max_features: The float value that the highest quantized value represents.

Returns:

  • Output activations: Has the same output shape as "features".
  • Output min_activations: The float value that the lowest quantized value represents.
  • Output max_activations: The float value that the highest quantized value represents.
Constructors and Destructors
QuantizedReluX(const ::tensorflow::Scope & scope, ::tensorflow::Input features, ::tensorflow::Input max_value, ::tensorflow::Input min_features, ::tensorflow::Input max_features)
QuantizedReluX(const ::tensorflow::Scope & scope, ::tensorflow::Input features, ::tensorflow::Input max_value, ::tensorflow::Input min_features, ::tensorflow::Input max_features, const QuantizedReluX::Attrs & attrs)
Public attributes
activations
max_activations
min_activations
Public static functions
OutType(DataType x)
Structs
tensorflow::ops::QuantizedReluX::Attrs

Optional attribute setters for QuantizedReluX.

Public attributes

activations

::tensorflow::Output activations

max_activations

::tensorflow::Output max_activations

min_activations

::tensorflow::Output min_activations

Public functions

QuantizedReluX

 QuantizedReluX(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input features,
  ::tensorflow::Input max_value,
  ::tensorflow::Input min_features,
  ::tensorflow::Input max_features
)

QuantizedReluX

 QuantizedReluX(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input features,
  ::tensorflow::Input max_value,
  ::tensorflow::Input min_features,
  ::tensorflow::Input max_features,
  const QuantizedReluX::Attrs & attrs
)

Public static functions

OutType

Attrs OutType(
  DataType x
)

© 2017 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/api_docs/cc/class/tensorflow/ops/quantized-relu-x.html

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