tensorflow::ops::FakeQuantWithMinMaxVars

#include <array_ops.h>

Fake-quantize the 'inputs' tensor of type float via global float scalars min

Summary

and max to 'outputs' tensor of same shape as inputs.

[min; max] define the clamping range for the inputs data. inputs values are quantized into the quantization range ([0; 2^num_bits - 1] when narrow_range is false and [1; 2^num_bits - 1] when it is true) and then de-quantized and output as floats in [min; max] interval. num_bits is the bitwidth of the quantization; between 2 and 16, inclusive.

This operation has a gradient and thus allows for training min and max values.

Arguments:

• scope: A Scope object

Returns:

• Output: The outputs tensor.

Public attributes

::tensorflow::Output outputs

Public functions

 FakeQuantWithMinMaxVars(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input inputs,
  ::tensorflow::Input min,
  ::tensorflow::Input max
)

 FakeQuantWithMinMaxVars(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input inputs,
  ::tensorflow::Input min,
  ::tensorflow::Input max,
  const FakeQuantWithMinMaxVars::Attrs & attrs
)

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const 

Public static functions

Attrs NarrowRange(
  bool x
)

Attrs NumBits(
  int64 x
)