FakeQuantWithMinMaxVarsPerChannel

tensorflow C++ API

tensorflow::ops::FakeQuantWithMinMaxVarsPerChannel

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

Summary

[b, d][b, h, w, d]via per-channel floatsminandmaxof shape[d]to 'outputs' tensor of same shape asinputs.

[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 trainingminandmaxvalues.

Arguments:

• scope: A Scope object

Returns:

• Output: The outputs tensor.

FakeQuantWithMinMaxVarsPerChannel block

Source link :https://github.com/EXPNUNI/enuSpaceTensorflow/blob/master/enuSpaceTensorflow/tf_array_ops.cpp

Argument:

• Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
• Input inputs: A Tensor of type float.
• Input min : A Tensor of type float.
• Input max : A Tensor of type float.
• Attr attrs : An optional attribute value
  • num_bits : An optional int. Defaults to 8.

Attrs use ex)

Output:

• output : Output object of FakeQuantWithMinMaxVarsPerChannel class object.

Result:

• std::vector(Tensor) result_output: A Tensor of type float. This operation has a gradient and thus allows for training min and max values.

Using Method