tf.raw_ops.SparseTensorDenseMatMul
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Multiply SparseTensor (of rank 2) "A" by dense matrix "B".
View aliases
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.
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.SparseTensorDenseMatMul\n\n\u003cbr /\u003e\n\nMultiply SparseTensor (of rank 2) \"A\" by dense matrix \"B\".\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.SparseTensorDenseMatMul`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SparseTensorDenseMatMul)\n\n\u003cbr /\u003e\n\n tf.raw_ops.SparseTensorDenseMatMul(\n a_indices,\n a_values,\n a_shape,\n b,\n adjoint_a=False,\n adjoint_b=False,\n name=None\n )\n\nNo validity checking is performed on the indices of A. However, the following\ninput format is recommended for optimal behavior:\n\nif adjoint_a == false:\nA should be sorted in lexicographically increasing order. Use SparseReorder\nif you're not sure.\nif adjoint_a == true:\nA should be sorted in order of increasing dimension 1 (i.e., \"column major\"\norder instead of \"row major\" order).\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `a_indices` | A `Tensor`. Must be one of the following types: `int32`, `int64`. 2-D. The `indices` of the `SparseTensor`, size `[nnz, 2]` Matrix. |\n| `a_values` | A `Tensor`. 1-D. The `values` of the `SparseTensor`, size `[nnz]` Vector. |\n| `a_shape` | A `Tensor` of type `int64`. 1-D. The `shape` of the `SparseTensor`, size `[2]` Vector. |\n| `b` | A `Tensor`. Must have the same type as `a_values`. 2-D. A dense Matrix. |\n| `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). |\n| `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). |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor`. Has the same type as `a_values`. ||\n\n\u003cbr /\u003e"]]
