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# tf.raw_ops.SparseTensorDenseMatMul

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

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).

`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).

A `Tensor`. Has the same type as `a_values`.

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