org.nd4j.linalg.api.ops.random.impl.AlphaDropOut Maven / Gradle / Ivy
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.nd4j.linalg.api.ops.random.impl;
import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.random.BaseRandomOp;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
/**
* AlphaDropOut implementation as Op
*
* @author [email protected]
*/
public class AlphaDropOut extends BaseRandomOp {
private double p;
private double a;
private double alphaPrime;
private double b;
public AlphaDropOut() {
}
public AlphaDropOut(@NonNull INDArray x, double p, double alpha, double alphaPrime, double beta) {
this(x, x, p, alpha, alphaPrime, beta);
}
public AlphaDropOut(@NonNull INDArray x, @NonNull INDArray z, double p, double alpha, double alphaPrime, double beta) {
super(x,null,z);
this.p = p;
this.a = alpha;
this.b = beta;
this.alphaPrime = alphaPrime;
this.extraArgs = new Object[] {p, a, b, alphaPrime};
}
@Override
public int opNum() {
return 12;
}
@Override
public String opName() {
return "alpha_dropout";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
throw new NoOpNameFoundException("No tensorflow op opName found for " + opName());
}
@Override
public List doDiff(List f1) {
return null;
}
}