ResourceApplyAdagradDa

public final class ResourceApplyAdagradDa

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

Nested Classes

class ResourceApplyAdagradDa.Options Optional attributes for ResourceApplyAdagradDa  

Constants

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

Public Methods

static <T extends TType> ResourceApplyAdagradDa
create(Scope scope, Operand<?> var, Operand<?> gradientAccumulator, Operand<?> gradientSquaredAccumulator, Operand<T> grad, Operand<T> lr, Operand<T> l1, Operand<T> l2, Operand<TInt64> globalStep, Options... options)
Factory method to create a class wrapping a new ResourceApplyAdagradDa operation.
static ResourceApplyAdagradDa.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: "ResourceApplyAdagradDA"

Public Methods

public static ResourceApplyAdagradDa create (Scope scope, Operand<?> var, Operand<?> gradientAccumulator, Operand<?> gradientSquaredAccumulator, Operand<T> grad, Operand<T> lr, Operand<T> l1, Operand<T> l2, Operand<TInt64> globalStep, Options... options)

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

Parameters
scope current 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

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.