org.tensorflow.op.core

Class ResourceApplyAdagradDA

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.ResourceApplyAdagradDA

All Implemented Interfaces:

Op

@Operator
public final class ResourceApplyAdagradDA
extends PrimitiveOp

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

Nested Class Summary

Nested Classes

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

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
static <T> ResourceApplyAdagradDA	create(Scope scope, Operand<?> var, Operand<?> gradientAccumulator, Operand<?> gradientSquaredAccumulator, Operand<T> grad, Operand<T> lr, Operand<T> l1, Operand<T> l2, Operand<Long> globalStep, ResourceApplyAdagradDA.Options... options) Factory method to create a class to wrap a new ResourceApplyAdagradDA operation to the graph.
static ResourceApplyAdagradDA.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> ResourceApplyAdagradDA create(Scope scope,
                                                Operand<?> var,
                                                Operand<?> gradientAccumulator,
                                                Operand<?> gradientSquaredAccumulator,
                                                Operand<T> grad,
                                                Operand<T> lr,
                                                Operand<T> l1,
                                                Operand<T> l2,
                                                Operand<Long> globalStep,
                                                ResourceApplyAdagradDA.Options... options)

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

Parameters:

scope - current graph 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

useLocking

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.