SparseApplyFtrl

public final class SparseApplyFtrl

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 * grad 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 SparseApplyFtrl.Options Optional attributes for SparseApplyFtrl  

Constants

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

Public Methods

Output<T>
asOutput()
Returns the symbolic handle of the tensor.
static <T extends TType> SparseApplyFtrl<T>
create(Scope scope, Operand<T> var, Operand<T> accum, Operand<T> 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 SparseApplyFtrl operation.
static SparseApplyFtrl.Options
multiplyLinearByLr(Boolean multiplyLinearByLr)
Output<T>
out()
Same as "var".
static SparseApplyFtrl.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.
org.tensorflow.Operand
abstract Output<T>
asOutput()
Returns the symbolic handle of the tensor.
abstract T
asTensor()
Returns the tensor at this operand.
abstract Shape
shape()
Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.
abstract Class<T>
type()
Returns the tensor type of this operand
org.tensorflow.ndarray.Shaped
abstract int
rank()
abstract Shape
shape()
abstract long
size()
Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

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

Constant Value: "SparseApplyFtrlV2"

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static SparseApplyFtrl<T> create (Scope scope, Operand<T> var, Operand<T> accum, Operand<T> 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 SparseApplyFtrl 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 SparseApplyFtrl

public static SparseApplyFtrl.Options multiplyLinearByLr (Boolean multiplyLinearByLr)

public Output<T> out ()

Same as "var".

public static SparseApplyFtrl.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.