ResourceSparseApplyAdagradV2

public final class ResourceSparseApplyAdagradV2

Update relevant entries in '*var' and '*accum' according to the adagrad scheme.

That is for rows we have grad for, we update var and accum as follows: accum += grad * grad var -= lr * grad * (1 / sqrt(accum))

Nested Classes

class

ResourceSparseApplyAdagradV2.Options

Optional attributes for ResourceSparseApplyAdagradV2

Public Methods

static <T, U extends Number> ResourceSparseApplyAdagradV2	create(Scope scope, Operand<?> var, Operand<?> accum, Operand<T> lr, Operand<T> epsilon, Operand<T> grad, Operand<U> indices, Options... options) Factory method to create a class wrapping a new ResourceSparseApplyAdagradV2 operation.
static ResourceSparseApplyAdagradV2.Options	updateSlots(Boolean updateSlots)
static ResourceSparseApplyAdagradV2.Options	useLocking(Boolean useLocking)

Inherited Methods

From class org.tensorflow.op.PrimitiveOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Returns the underlying 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()

Public Methods

public static ResourceSparseApplyAdagradV2 create (Scope scope, Operand<?> var, Operand<?> accum, Operand<T> lr, Operand<T> epsilon, Operand<T> grad, Operand<U> indices, Options... options)

Factory method to create a class wrapping a new ResourceSparseApplyAdagradV2 operation.

Parameters

scope	current scope
var	Should be from a Variable().
accum	Should be from a Variable().
lr	Learning rate. Must be a scalar.
epsilon	Constant factor. Must be a scalar.
grad	The gradient.
indices	A vector of indices into the first dimension of var and accum.
options	carries optional attributes values

Returns

• a new instance of ResourceSparseApplyAdagradV2

public static ResourceSparseApplyAdagradV2.Options updateSlots (Boolean updateSlots)

public static ResourceSparseApplyAdagradV2.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.