ResourceSparseApplyAdagrad

public final class ResourceSparseApplyAdagrad

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 ResourceSparseApplyAdagrad.Options Optional attributes for ResourceSparseApplyAdagrad

Constants

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

Public Methods

static <T extends TType > ResourceSparseApplyAdagrad
create ( Scope scope, Operand <?> var, Operand <?> accum, Operand <T> lr, Operand <T> grad, Operand <? extends TNumber > indices, Options... options)
Factory method to create a class wrapping a new ResourceSparseApplyAdagrad operation.
static ResourceSparseApplyAdagrad.Options
updateSlots (Boolean updateSlots)
static ResourceSparseApplyAdagrad.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: "ResourceSparseApplyAdagrad"

Public Methods

public static ResourceSparseApplyAdagrad create ( Scope scope, Operand <?> var, Operand <?> accum, Operand <T> lr, Operand <T> grad, Operand <? extends TNumber > indices, Options... options)

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

Parameters
scope current scope
var Should be from a Variable().
accum Should be from a Variable().
lr Learning rate. 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 ResourceSparseApplyAdagrad

public static ResourceSparseApplyAdagrad.Options updateSlots (Boolean updateSlots)

public static ResourceSparseApplyAdagrad.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.