ResourceSparseApplyAdagradDa

public final class ResourceSparseApplyAdagradDa

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

class ResourceSparseApplyAdagradDa.Options Optional attributes for ResourceSparseApplyAdagradDa

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

static <T extends TType> ResourceSparseApplyAdagradDa	create(Scope scope, Operand<?> var, Operand<?> gradientAccumulator, Operand<?> gradientSquaredAccumulator, Operand<T> grad, Operand<? extends TNumber> indices, Operand<T> lr, Operand<T> l1, Operand<T> l2, Operand<TInt64> globalStep, Options... options) Factory method to create a class wrapping a new ResourceSparseApplyAdagradDa operation.
static ResourceSparseApplyAdagradDa.Options	useLocking(Boolean useLocking)

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

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

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

Constant Value: "ResourceSparseApplyAdagradDA"

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

scope	current scope
var	Should be from a Variable().
gradientAccumulator	Should be from a Variable().
gradientSquaredAccumulator	Should be from a Variable().
grad	The gradient.
indices	A vector of indices into the first dimension of var and accum.
lr	Learning rate. 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

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.