ResourceApplyAdagradDa

public final class ResourceApplyAdagradDa

Update '*var' according to the proximal adagrad scheme.

Nested Classes

class

ResourceApplyAdagradDa.Options

Optional attributes for ResourceApplyAdagradDa

Constants

String

OP_NAME

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

Public Methods

static <T extends TType> ResourceApplyAdagradDa	create(Scope scope, Operand<?> var, Operand<?> gradientAccumulator, Operand<?> gradientSquaredAccumulator, Operand<T> grad, Operand<T> lr, Operand<T> l1, Operand<T> l2, Operand<TInt64> globalStep, Options... options) Factory method to create a class wrapping a new ResourceApplyAdagradDa operation.
static ResourceApplyAdagradDa.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: "ResourceApplyAdagradDA"

Public Methods

public static ResourceApplyAdagradDa create (Scope scope, Operand<?> var, Operand<?> gradientAccumulator, Operand<?> gradientSquaredAccumulator, Operand<T> grad, Operand<T> lr, Operand<T> l1, Operand<T> l2, Operand<TInt64> globalStep, Options... options)

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

Parameters

scope	current scope
var	Should be from a Variable().
gradientAccumulator	Should be from a Variable().
gradientSquaredAccumulator	Should be from a Variable().
grad	The gradient.
lr	Scaling factor. Must be a scalar.
l1	L1 regularization. Must be a scalar.
l2	L2 regularization. Must be a scalar.
globalStep	Training step number. Must be a scalar.
options	carries optional attributes values

Returns

• a new instance of ResourceApplyAdagradDa

public static ResourceApplyAdagradDa.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.