ResourceApplyAdagradDa

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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

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.