ResourceApplyAdaMax

public final class ResourceApplyAdaMax

Update '*var' according to the AdaMax algorithm.

m_t <- beta1 * m_{t-1} + (1 - beta1) * g v_t <- max(beta2 * v_{t-1}, abs(g)) variable <- variable - learning_rate / (1 - beta1^t) * m_t / (v_t + epsilon)

Nested Classes

class ResourceApplyAdaMax.Options Optional attributes for ResourceApplyAdaMax

Constants

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

Public Methods

static <T extends TType> ResourceApplyAdaMax	create(Scope scope, Operand<?> var, Operand<?> m, Operand<?> v, Operand<T> beta1Power, Operand<T> lr, Operand<T> beta1, Operand<T> beta2, Operand<T> epsilon, Operand<T> grad, Options... options) Factory method to create a class wrapping a new ResourceApplyAdaMax operation.
static ResourceApplyAdaMax.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: "ResourceApplyAdaMax"

Public Methods

public static ResourceApplyAdaMax create (Scope scope, Operand<?> var, Operand<?> m, Operand<?> v, Operand<T> beta1Power, Operand<T> lr, Operand<T> beta1, Operand<T> beta2, Operand<T> epsilon, Operand<T> grad, Options... options)

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

Parameters

scope	current scope
var	Should be from a Variable().
m	Should be from a Variable().
v	Should be from a Variable().
beta1Power	Must be a scalar.
lr	Scaling factor. Must be a scalar.
beta1	Momentum factor. Must be a scalar.
beta2	Momentum factor. Must be a scalar.
epsilon	Ridge term. Must be a scalar.
grad	The gradient.
options	carries optional attributes values

Returns

a new instance of ResourceApplyAdaMax

public static ResourceApplyAdaMax.Options useLocking (Boolean useLocking)

Parameters

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