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

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()
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()
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.