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tensorflow::ops::QuantizedReluX
#include <nn_ops.h>
Computes Quantized Rectified Linear X: min(max(features, 0), max_value)
Summary
Args:
- 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 | |
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QuantizedReluX(const ::tensorflow::Scope & scope, ::tensorflow::Input features, ::tensorflow::Input max_value, ::tensorflow::Input min_features, ::tensorflow::Input max_features) |
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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 | |
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activations |
|
max_activations |
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min_activations |
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operation |
Structs | |
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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
operation
Operation operation
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
)
© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/cc/class/tensorflow/ops/quantized-relu-x