org.tensorflow.op.core

Class SparseApplyAdagrad<T>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.SparseApplyAdagrad<T>

Type Parameters:

T - data type for out() output

All Implemented Interfaces:

Op, Operand<T>

@Operator
public final class SparseApplyAdagrad<T>
extends PrimitiveOp
implements Operand<T>

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 Class Summary

Nested Classes

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

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> SparseApplyAdagrad<T>	create(Scope scope, Operand<T> var, Operand<T> accum, Operand<T> lr, Operand<T> grad, Operand<U> indices, SparseApplyAdagrad.Options... options) Factory method to create a class to wrap a new SparseApplyAdagrad operation to the graph.
Output<T>	out() Same as "var".
static SparseApplyAdagrad.Options	updateSlots(Boolean updateSlots)
static SparseApplyAdagrad.Options	useLocking(Boolean useLocking)

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, 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> SparseApplyAdagrad<T> create(Scope scope,
                                                                Operand<T> var,
                                                                Operand<T> accum,
                                                                Operand<T> lr,
                                                                Operand<T> grad,
                                                                Operand<U> indices,
                                                                SparseApplyAdagrad.Options... options)

Factory method to create a class to wrap a new SparseApplyAdagrad operation to the graph.

Parameters:

scope - current graph 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 SparseApplyAdagrad

useLocking

public static SparseApplyAdagrad.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.

updateSlots

public static SparseApplyAdagrad.Options updateSlots(Boolean updateSlots)

Parameters:

updateSlots -

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)