org.tensorflow.op.train

Class SparseApplyAdagradDa<T>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.train.SparseApplyAdagradDa<T>

Type Parameters:

T - data type for out() output

All Implemented Interfaces:

Op, Operand<T>

@Operator(group="train")
public final class SparseApplyAdagradDa<T>
extends PrimitiveOp
implements Operand<T>

Update entries in '*var' and '*accum' according to the proximal adagrad scheme.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SparseApplyAdagradDa.Options Optional attributes for SparseApplyAdagradDa

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
Output<T>	asOutput() Returns the symbolic handle of a tensor.
static <T,U extends Number> SparseApplyAdagradDa<T>	create(Scope scope, Operand<T> var, Operand<T> gradientAccumulator, Operand<T> gradientSquaredAccumulator, Operand<T> grad, Operand<U> indices, Operand<T> lr, Operand<T> l1, Operand<T> l2, Operand<Long> globalStep, SparseApplyAdagradDa.Options... options) Factory method to create a class wrapping a new SparseApplyAdagradDa operation.
Output<T>	out() Same as "var".
static SparseApplyAdagradDa.Options	useLocking(Boolean useLocking)

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, op, toString

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Method Detail

create

public static <T,U extends Number> SparseApplyAdagradDa<T> create(Scope scope,
                                                                  Operand<T> var,
                                                                  Operand<T> gradientAccumulator,
                                                                  Operand<T> gradientSquaredAccumulator,
                                                                  Operand<T> grad,
                                                                  Operand<U> indices,
                                                                  Operand<T> lr,
                                                                  Operand<T> l1,
                                                                  Operand<T> l2,
                                                                  Operand<Long> globalStep,
                                                                  SparseApplyAdagradDa.Options... options)

Factory method to create a class wrapping a new SparseApplyAdagradDa 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.

indices - A vector of indices into the first dimension of var and accum.

lr - Learning rate. 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 SparseApplyAdagradDa

useLocking

public static SparseApplyAdagradDa.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.

out

public Output<T> out()

Same as "var".

asOutput

public Output<T> asOutput()

Description copied from interface: Operand

Returns the symbolic handle of a 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.

Specified by:

asOutput in interface Operand<T>

See Also:

OperationBuilder.addInput(Output)