FakeQuantWithMinMaxVars

tensorflow C++ API

tensorflow::ops::FakeQuantWithMinMaxVars

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

Summary

andmaxto 'outputs' tensor of same shape asinputs.

[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 trainingminandmaxvalues.

Arguments:

• scope: A Scope object

Returns:

• Output : The outputs tensor.

FakeQuantWithMinMaxVars 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 FakeQuantWithMinMaxVars class object.

Result:

• std::vector(Tensor) result_output : A Tensor of type float

Using Method