SparseMatMul

public final class SparseMatMul

Multiply matrix "a" by matrix "b".

The inputs must be two-dimensional matrices and the inner dimension of "a" must match the outer dimension of "b". Both "a" and "b" must be `Tensor`s not `SparseTensor`s. This op is optimized for the case where at least one of "a" or "b" is sparse, in the sense that they have a large proportion of zero values. The breakeven for using this versus a dense matrix multiply on one platform was 30% zero values in the sparse matrix.

The gradient computation of this operation will only take advantage of sparsity in the input gradient when that gradient comes from a Relu.

Nested Classes

class

SparseMatMul.Options

Optional attributes for SparseMatMul

Constants

String

OP_NAME

The name of this op, as known by TensorFlow core engine

Public Methods

static SparseMatMul.Options	aIsSparse(Boolean aIsSparse)
Output<TFloat32>	asOutput() Returns the symbolic handle of the tensor.
static SparseMatMul.Options	bIsSparse(Boolean bIsSparse)
static SparseMatMul	create(Scope scope, Operand<? extends TNumber> a, Operand<? extends TNumber> b, Options... options) Factory method to create a class wrapping a new SparseMatMul operation.
Output<TFloat32>	product()
static SparseMatMul.Options	transposeA(Boolean transposeA)
static SparseMatMul.Options	transposeB(Boolean transposeB)

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single Operation.
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single Operation.

From interface org.tensorflow.Operand

abstract Output<TFloat32>	asOutput() Returns the symbolic handle of the tensor.
abstract TFloat32	asTensor() Returns the tensor at this operand.
abstract Shape	shape() Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.
abstract Class<TFloat32>	type() Returns the tensor type of this operand

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "SparseMatMul"

Public Methods

public static SparseMatMul.Options aIsSparse (Boolean aIsSparse)

public Output<TFloat32> asOutput ()

Returns the symbolic handle of the tensor.

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.

public static SparseMatMul.Options bIsSparse (Boolean bIsSparse)

public static SparseMatMul create (Scope scope, Operand<? extends TNumber> a, Operand<? extends TNumber> b, Options... options)

Factory method to create a class wrapping a new SparseMatMul operation.

Parameters

scope	current scope
options	carries optional attributes values

Returns

• a new instance of SparseMatMul

public Output<TFloat32> product ()

public static SparseMatMul.Options transposeA (Boolean transposeA)

public static SparseMatMul.Options transposeB (Boolean transposeB)