U
- data type for product()
output@Operator(group="sparse") public final class SparseTensorDenseMatMul<U> extends PrimitiveOp implements Operand<U>
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).
Modifier and Type | Class and Description |
---|---|
static class |
SparseTensorDenseMatMul.Options
Optional attributes for
SparseTensorDenseMatMul |
operation
Modifier and Type | Method and Description |
---|---|
static SparseTensorDenseMatMul.Options |
adjointA(Boolean adjointA) |
static SparseTensorDenseMatMul.Options |
adjointB(Boolean adjointB) |
Output<U> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <U,T extends Number> |
create(Scope scope,
Operand<T> aIndices,
Operand<U> aValues,
Operand<Long> aShape,
Operand<U> b,
SparseTensorDenseMatMul.Options... options)
Factory method to create a class wrapping a new SparseTensorDenseMatMul operation.
|
Output<U> |
product() |
equals, hashCode, op, toString
public static <U,T extends Number> SparseTensorDenseMatMul<U> create(Scope scope, Operand<T> aIndices, Operand<U> aValues, Operand<Long> aShape, Operand<U> b, SparseTensorDenseMatMul.Options... options)
scope
- current scopeaIndices
- 2-D. The `indices` of the `SparseTensor`, size `[nnz, 2]` Matrix.aValues
- 1-D. The `values` of the `SparseTensor`, size `[nnz]` Vector.aShape
- 1-D. The `shape` of the `SparseTensor`, size `[2]` Vector.b
- 2-D. A dense Matrix.options
- carries optional attributes valuespublic static SparseTensorDenseMatMul.Options adjointA(Boolean adjointA)
adjointA
- Use the adjoint of A in the matrix multiply. If A is complex, this
is transpose(conj(A)). Otherwise it's transpose(A).public static SparseTensorDenseMatMul.Options adjointB(Boolean adjointB)
adjointB
- Use the adjoint of B in the matrix multiply. If B is complex, this
is transpose(conj(B)). Otherwise it's transpose(B).public Output<U> asOutput()
Operand
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
asOutput
in interface Operand<U>
OperationBuilder.addInput(Output)
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