org.tensorflow.op.train.ResourceSparseApplyAdadelta Maven / Gradle / Ivy
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/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
=======================================================================*/
// This class has been generated, DO NOT EDIT!
package org.tensorflow.op.train;
import org.tensorflow.Operand;
import org.tensorflow.Operation;
import org.tensorflow.OperationBuilder;
import org.tensorflow.op.PrimitiveOp;
import org.tensorflow.op.Scope;
import org.tensorflow.op.annotation.Operator;
/**
* var: Should be from a Variable().
*/
@Operator(group = "train")
public final class ResourceSparseApplyAdadelta extends PrimitiveOp {
/**
* Optional attributes for {@link org.tensorflow.op.train.ResourceSparseApplyAdadelta}
*/
public static class Options {
/**
* @param 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.
*/
public Options useLocking(Boolean useLocking) {
this.useLocking = useLocking;
return this;
}
private Boolean useLocking;
private Options() {
}
}
/**
* Factory method to create a class wrapping a new ResourceSparseApplyAdadelta operation.
*
* @param scope current scope
* @param var
* @param accum Should be from a Variable().
* @param accumUpdate : Should be from a Variable().
* @param lr Learning rate. Must be a scalar.
* @param rho Decay factor. Must be a scalar.
* @param epsilon Constant factor. Must be a scalar.
* @param grad The gradient.
* @param indices A vector of indices into the first dimension of var and accum.
* @param options carries optional attributes values
* @return a new instance of ResourceSparseApplyAdadelta
*/
public static ResourceSparseApplyAdadelta create(Scope scope, Operand var, Operand accum, Operand accumUpdate, Operand lr, Operand rho, Operand epsilon, Operand grad, Operand indices, Options... options) {
OperationBuilder opBuilder = scope.env().opBuilder("ResourceSparseApplyAdadelta", scope.makeOpName("ResourceSparseApplyAdadelta"));
opBuilder.addInput(var.asOutput());
opBuilder.addInput(accum.asOutput());
opBuilder.addInput(accumUpdate.asOutput());
opBuilder.addInput(lr.asOutput());
opBuilder.addInput(rho.asOutput());
opBuilder.addInput(epsilon.asOutput());
opBuilder.addInput(grad.asOutput());
opBuilder.addInput(indices.asOutput());
opBuilder = scope.applyControlDependencies(opBuilder);
if (options != null) {
for (Options opts : options) {
if (opts.useLocking != null) {
opBuilder.setAttr("use_locking", opts.useLocking);
}
}
}
return new ResourceSparseApplyAdadelta(opBuilder.build());
}
/**
* @param 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.
*/
public static Options useLocking(Boolean useLocking) {
return new Options().useLocking(useLocking);
}
private ResourceSparseApplyAdadelta(Operation operation) {
super(operation);
}
}