ResourceSparseApplyFtrl

public final class ResourceSparseApplyFtrl

Update relevant entries in '*var' according to the Ftrl-proximal scheme.

That is for rows we have grad for, we update var, accum and linear as follows: grad_with_shrinkage = grad + 2 * l2_shrinkage * var accum_new = accum + grad_with_shrinkage * grad_with_shrinkage linear += grad_with_shrinkage + (accum_new^(-lr_power) - accum^(-lr_power)) / lr * var quadratic = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2 var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0 accum = accum_new

Nested Classes

class ResourceSparseApplyFtrl.Options Optional attributes for ResourceSparseApplyFtrl  

Constants

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

Public Methods

static <T extends TType> ResourceSparseApplyFtrl
create(Scope scope, Operand<?> var, Operand<?> accum, Operand<?> linear, Operand<T> grad, Operand<? extends TNumber> indices, Operand<T> lr, Operand<T> l1, Operand<T> l2, Operand<T> l2Shrinkage, Operand<T> lrPower, Options... options)
Factory method to create a class wrapping a new ResourceSparseApplyFtrl operation.
static ResourceSparseApplyFtrl.Options
multiplyLinearByLr(Boolean multiplyLinearByLr)
static ResourceSparseApplyFtrl.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: "ResourceSparseApplyFtrlV2"

Public Methods

public static ResourceSparseApplyFtrl create (Scope scope, Operand<?> var, Operand<?> accum, Operand<?> linear, Operand<T> grad, Operand<? extends TNumber> indices, Operand<T> lr, Operand<T> l1, Operand<T> l2, Operand<T> l2Shrinkage, Operand<T> lrPower, Options... options)

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

Parameters
scope current scope
var Should be from a Variable().
accum Should be from a Variable().
linear Should be from a Variable().
grad The gradient.
indices A vector of indices into the first dimension of var and accum.
lr Scaling factor. Must be a scalar.
l1 L1 regularization. Must be a scalar.
l2 L2 shrinkage regularization. Must be a scalar.
lrPower Scaling factor. Must be a scalar.
options carries optional attributes values
Returns
  • a new instance of ResourceSparseApplyFtrl

public static ResourceSparseApplyFtrl.Options multiplyLinearByLr (Boolean multiplyLinearByLr)

public static ResourceSparseApplyFtrl.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.