SparseApplyMomentum

public final class SparseApplyMomentum

Update relevant entries in '*var' and '*accum' according to the momentum scheme.

Set use_nesterov = True if you want to use Nesterov momentum.

That is for rows we have grad for, we update var and accum as follows:

$$accum = accum * momentum + grad$$ $$var -= lr * accum$$

Nested Classes

class

SparseApplyMomentum.Options

Optional attributes for SparseApplyMomentum

Constants

String

OP_NAME

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

Public Methods

Output<T>	asOutput() Returns the symbolic handle of the tensor.
static <T extends TType> SparseApplyMomentum<T>	create(Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> grad, Operand<? extends TNumber> indices, Operand<T> momentum, Options... options) Factory method to create a class wrapping a new SparseApplyMomentum operation.
Output<T>	out() Same as "var".
static SparseApplyMomentum.Options	useLocking(Boolean useLocking)
static SparseApplyMomentum.Options	useNesterov(Boolean useNesterov)

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<T>	asOutput() Returns the symbolic handle of the tensor.
abstract T	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<T>	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: "SparseApplyMomentum"

Public Methods

public Output<T> 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 SparseApplyMomentum<T> create (Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> grad, Operand<? extends TNumber> indices, Operand<T> momentum, Options... options)

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

Parameters

scope	current scope
var	Should be from a Variable().
accum	Should be from a Variable().
lr	Learning rate. Must be a scalar.
grad	The gradient.
indices	A vector of indices into the first dimension of var and accum.
momentum	Momentum. Must be a scalar.
options	carries optional attributes values

Returns

• a new instance of SparseApplyMomentum

public Output<T> out ()

Same as "var".

public static SparseApplyMomentum.Options useLocking (Boolean useLocking)

Parameters

useLocking	If `True`, updating of the var and accum tensors will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.

public static SparseApplyMomentum.Options useNesterov (Boolean useNesterov)

Parameters

useNesterov	If `True`, the tensor passed to compute grad will be var - lr * momentum * accum, so in the end, the var you get is actually var - lr * momentum * accum.