tensorflow::ops::SparseMatMul

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.

Args:

• scope: A Scope object

Returns:

• Output: The product tensor.

Public attributes

Operation operation

::tensorflow::Output product

Public functions

 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
)

::tensorflow::Node * node() const 

 operator::tensorflow::Input() const 

 operator::tensorflow::Output() const 

Public static functions

Attrs AIsSparse(
  bool x
)

Attrs BIsSparse(
  bool x
)

Attrs TransposeA(
  bool x
)

Attrs TransposeB(
  bool x
)