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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).

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.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/SparseTensorDenseMatMul