Warning: This API is deprecated and will be removed in a future version of TensorFlow after the replacement is stable.

SparseApplyAdagradV2

public final class SparseApplyAdagradV2

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 SparseApplyAdagradV2.Options Optional attributes for SparseApplyAdagradV2

Public Methods

Output<T>	asOutput() Returns the symbolic handle of a tensor.
static <T, U extends Number> SparseApplyAdagradV2<T>	create(Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> epsilon, Operand<T> grad, Operand<U> indices, Options... options) Factory method to create a class wrapping a new SparseApplyAdagradV2 operation.
Output<T>	out() Same as "var".
static SparseApplyAdagradV2.Options	updateSlots(Boolean updateSlots)
static SparseApplyAdagradV2.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()

From interface org.tensorflow.Operand

abstract Output<T>

asOutput()

Returns the symbolic handle of a tensor.

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static SparseApplyAdagradV2<T> create (Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> epsilon, Operand<T> grad, Operand<U> indices, Options... options)

Factory method to create a class wrapping a new SparseApplyAdagradV2 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 SparseApplyAdagradV2

public Output<T> out ()

Same as "var".

public static SparseApplyAdagradV2.Options updateSlots (Boolean updateSlots)

public static SparseApplyAdagradV2.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.