ResourceApplyProximalAdagrad

public final class ResourceApplyProximalAdagrad

Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.

accum += grad grad prox_v = var - lr grad (1 / sqrt(accum)) var = sign(prox_v)/(1+lrl2) max{|prox_v|-lrl1,0}

class ResourceApplyProximalAdagrad.Options Optional attributes for ResourceApplyProximalAdagrad

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

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

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

scope	current scope
var	Should be from a Variable().
accum	Should be from a Variable().
lr	Scaling factor. Must be a scalar.
l1	L1 regularization. Must be a scalar.
l2	L2 regularization. Must be a scalar.
grad	The gradient.
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.