#include <array_ops.h>
Fake-quantize the 'inputs' tensor of type float and shape [b, h, w, d] via.
global float scalars min and max to 'outputs' tensor of same shape as inputs.
[min; max] is the clamping range for the 'inputs' data. Op divides this range into 255 steps (total of 256 values), then replaces each 'inputs' value with the closest of the quantized step values.
This operation has a gradient and thus allows for training min and max values.
Arguments:
Returns:
Output: The outputs tensor. | Constructors and Destructors | |
|---|---|
FakeQuantWithMinMaxVars(const ::tensorflow::Scope & scope, ::tensorflow::Input inputs, ::tensorflow::Input min, ::tensorflow::Input max) |
| Public attributes | |
|---|---|
outputs | |
| Public functions | |
|---|---|
node() const | ::tensorflow::Node * |
operator::tensorflow::Input() const | |
operator::tensorflow::Output() const | |
::tensorflow::Output outputs
FakeQuantWithMinMaxVars( const ::tensorflow::Scope & scope, ::tensorflow::Input inputs, ::tensorflow::Input min, ::tensorflow::Input max )
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output() const
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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/api_docs/cc/class/tensorflow/ops/fake-quant-with-min-max-vars.html