tensorflow::ops::SparseMatMul

#include <math_ops.h>

Multiply matrix "a" by matrix "b".

Summary

The inputs must be two-dimensional matrices and the inner dimension of "a" must match the outer dimension of "b". Both "a" and "b" must be Tensors not SparseTensors. This op is optimized for the case where at least one of "a" or "b" is sparse, in the sense that they have a large proportion of zero values. The breakeven for using this versus a dense matrix multiply on one platform was 30% zero values in the sparse matrix.

The gradient computation of this operation will only take advantage of sparsity in the input gradient when that gradient comes from a Relu.

Arguments:

Returns:

Constructors and Destructors

SparseMatMul(const ::tensorflow::Scope & scope, ::tensorflow::Input a, ::tensorflow::Input b)
SparseMatMul(const ::tensorflow::Scope & scope, ::tensorflow::Input a, ::tensorflow::Input b, const SparseMatMul::Attrs & attrs)

Public attributes

product

Public functions

node() const
::tensorflow::Node *
operator::tensorflow::Input() const
operator::tensorflow::Output() const

Public static functions

AIsSparse(bool x)
BIsSparse(bool x)
TransposeA(bool x)
TransposeB(bool x)

Structs

tensorflow::ops::SparseMatMul::Attrs

Optional attribute setters for SparseMatMul.

Public attributes

product

::tensorflow::Output product

Public functions

SparseMatMul

 SparseMatMul(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input a,
  ::tensorflow::Input b
)

SparseMatMul

 SparseMatMul(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input a,
  ::tensorflow::Input b,
  const SparseMatMul::Attrs & attrs
)

node

::tensorflow::Node * node() const 

operator::tensorflow::Input

 operator::tensorflow::Input() const 

operator::tensorflow::Output

 operator::tensorflow::Output() const 

Public static functions

AIsSparse

Attrs AIsSparse(
  bool x
)

BIsSparse

Attrs BIsSparse(
  bool x
)

TransposeA

Attrs TransposeA(
  bool x
)

TransposeB

Attrs TransposeB(
  bool x
)