tf.raw_ops.SparseTensorDenseMatMul

Multiply SparseTensor (of rank 2) "A" by dense matrix "B".

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.SparseTensorDenseMatMul

tf.raw_ops.SparseTensorDenseMatMul(
    a_indices, a_values, a_shape, b, adjoint_a=False, adjoint_b=False, name=None
)

No validity checking is performed on the indices of A. However, the following input format is recommended for optimal behavior:

if adjoint_a == false: A should be sorted in lexicographically increasing order. Use SparseReorder if you're not sure. if adjoint_a == true: A should be sorted in order of increasing dimension 1 (i.e., "column major" order instead of "row major" order).

Args
a_indices	A Tensor. Must be one of the following types: int32, int64. 2-D. The indices of the SparseTensor, size [nnz, 2] Matrix.
a_values	A Tensor. 1-D. The values of the SparseTensor, size [nnz] Vector.
a_shape	A Tensor of type int64. 1-D. The shape of the SparseTensor, size [2] Vector.
b	A Tensor. Must have the same type as a_values. 2-D. A dense Matrix.
adjoint_a	An optional bool. Defaults to False. Use the adjoint of A in the matrix multiply. If A is complex, this is transpose(conj(A)). Otherwise it's transpose(A).
adjoint_b	An optional bool. Defaults to False. Use the adjoint of B in the matrix multiply. If B is complex, this is transpose(conj(B)). Otherwise it's transpose(B).
name	A name for the operation (optional).

Returns
A Tensor. Has the same type as a_values.