org.tensorflow.op.core

Class SparseApplyMomentum<T>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.SparseApplyMomentum<T>

Type Parameters:

T - data type for out() output

All Implemented Interfaces:

Op, Operand<T>

@Operator
public final class SparseApplyMomentum<T>
extends PrimitiveOp
implements Operand<T>

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 Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SparseApplyMomentum.Options Optional attributes for SparseApplyMomentum

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
Output<T>	asOutput() Returns the symbolic handle of a tensor.
static <T,U extends Number> SparseApplyMomentum<T>	create(Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> grad, Operand<U> indices, Operand<T> momentum, SparseApplyMomentum.Options... options) Factory method to create a class to wrap a new SparseApplyMomentum operation to the graph.
Output<T>	out() Same as "var".
static SparseApplyMomentum.Options	useLocking(Boolean useLocking)
static SparseApplyMomentum.Options	useNesterov(Boolean useNesterov)

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, toString

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Method Detail

create

public static <T,U extends Number> SparseApplyMomentum<T> create(Scope scope,
                                                                 Operand<T> var,
                                                                 Operand<T> accum,
                                                                 Operand<T> lr,
                                                                 Operand<T> grad,
                                                                 Operand<U> indices,
                                                                 Operand<T> momentum,
                                                                 SparseApplyMomentum.Options... options)

Factory method to create a class to wrap a new SparseApplyMomentum operation to the graph.

Parameters:

scope - current graph 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

useLocking

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.

useNesterov

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.

out

public Output<T> out()

Same as "var".

asOutput

public Output<T> asOutput()

Description copied from interface: Operand

Returns the symbolic handle of a 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.

Specified by:

asOutput in interface Operand<T>

See Also:

OperationBuilder.addInput(Output)