tensorflow::ops::FakeQuantWithMinMaxVarsPerChannel

tensorflow::ops::FakeQuantWithMinMaxVarsPerChannel

#include <array_ops.h>

Fake-quantize the 'inputs' tensor of type float and one of the shapes: [d],.

Summary

[b, d][b, h, w, d] via per-channel floats min and max of shape [d] to 'outputs' tensor of same shape as inputs.

[min; max] is the clamping range for the 'inputs' data in the corresponding depth channel. 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

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

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

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const 

Public static functions

Attrs NumBits(
  int64 x
)