ResourceApplyProximalGradientDescent

public final class ResourceApplyProximalGradientDescent

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 Classes

class

ResourceApplyProximalGradientDescent.Options

Optional attributes for ResourceApplyProximalGradientDescent

Constants

String

OP_NAME

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

Public Methods

static <T extends TType> ResourceApplyProximalGradientDescent	create(Scope scope, Operand<?> var, Operand<T> alpha, Operand<T> l1, Operand<T> l2, Operand<T> delta, Options... options) Factory method to create a class wrapping a new ResourceApplyProximalGradientDescent operation.
static ResourceApplyProximalGradientDescent.Options	useLocking(Boolean useLocking)

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.

Constants

public static final String OP_NAME

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

Constant Value: "ResourceApplyProximalGradientDescent"

Public Methods

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

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

Parameters

scope	current 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

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.