tensorflow::ops::QuantizedMatMul

#include <math_ops.h>

Perform a quantized matrix multiplication of a by the matrix b.

Summary

The inputs must be two-dimensional matrices and the inner dimension of a (after being transposed if transpose_a is non-zero) must match the outer dimension of b (after being transposed if transposed_b is non-zero).

Arguments:

• scope: A Scope object
• a: Must be a two-dimensional tensor.
• b: Must be a two-dimensional tensor.
• min_a: The float value that the lowest quantized a value represents.
• max_a: The float value that the highest quantized a value represents.
• min_b: The float value that the lowest quantized b value represents.
• max_b: The float value that the highest quantized b value represents.

Optional attributes (see Attrs):

• transpose_a: If true, a is transposed before multiplication.
• transpose_b: If true, b is transposed before multiplication.
• Tactivation: The type of output produced by activation function following this operation.

Returns:

• Output out
• Output min_out: The float value that the lowest quantized output value represents.
• Output max_out: The float value that the highest quantized output value represents.

Public attributes

::tensorflow::Output max_out

::tensorflow::Output min_out

Operation operation

::tensorflow::Output out

Public functions

 QuantizedMatMul(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input a,
  ::tensorflow::Input b,
  ::tensorflow::Input min_a,
  ::tensorflow::Input max_a,
  ::tensorflow::Input min_b,
  ::tensorflow::Input max_b
)

 QuantizedMatMul(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input a,
  ::tensorflow::Input b,
  ::tensorflow::Input min_a,
  ::tensorflow::Input max_a,
  ::tensorflow::Input min_b,
  ::tensorflow::Input max_b,
  const QuantizedMatMul::Attrs & attrs
)

Public static functions

Attrs Tactivation(
  DataType x
)

Attrs Toutput(
  DataType x
)

Attrs TransposeA(
  bool x
)

Attrs TransposeB(
  bool x
)