tensorflow::ops::FakeQuantWithMinMaxVars

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] 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. 'num_bits' is the bitwidth of the quantization; between 2 and 8, 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 NumBits(
  int64 x
)