org.tensorflow.op.core

Class ResourceApplyProximalGradientDescent

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.ResourceApplyProximalGradientDescent

All Implemented Interfaces:

Op

@Operator
public final class ResourceApplyProximalGradientDescent
extends PrimitiveOp

Update '*var' as FOBOS algorithm with fixed learning rate.

prox_v = var - alpha delta var = sign(prox_v)/(1+alphal2) max{|prox_v|-alphal1,0}

Nested Class Summary

Nested Classes

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

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
static <T> ResourceApplyProximalGradientDescent	create(Scope scope, Operand<?> var, Operand<T> alpha, Operand<T> l1, Operand<T> l2, Operand<T> delta, ResourceApplyProximalGradientDescent.Options... options) Factory method to create a class to wrap a new ResourceApplyProximalGradientDescent operation to the graph.
static ResourceApplyProximalGradientDescent.Options	useLocking(Boolean useLocking)

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> ResourceApplyProximalGradientDescent create(Scope scope,
                                                              Operand<?> var,
                                                              Operand<T> alpha,
                                                              Operand<T> l1,
                                                              Operand<T> l2,
                                                              Operand<T> delta,
                                                              ResourceApplyProximalGradientDescent.Options... options)

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

Parameters:

scope - current graph scope

var - Should be from a Variable().

alpha - Scaling factor. Must be a scalar.

l1 - L1 regularization. Must be a scalar.

l2 - L2 regularization. Must be a scalar.

delta - The change.

options - carries optional attributes values

Returns:

a new instance of ResourceApplyProximalGradientDescent

useLocking

public static ResourceApplyProximalGradientDescent.Options useLocking(Boolean useLocking)

Parameters:

useLocking - If True, the subtraction will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.