org.nd4j.linalg.activations.impl.ActivationPReLU Maven / Gradle / Ivy
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* 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.activations.impl;
import lombok.EqualsAndHashCode;
import lombok.Getter;
import org.nd4j.linalg.activations.BaseActivationFunction;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.primitives.Pair;
/**
/** Parametrized Rectified Linear Unit (PReLU)
*
* f(x) = alpha * x for x < 0, f(x) = x for x >= 0
*
* alpha has the same shape as x and is a learned parameter.
*
* @author Max Pumperla
*/
@EqualsAndHashCode
@Getter
public class ActivationPReLU extends BaseActivationFunction {
private INDArray alpha;
private long[] sharedAxes = null;
public ActivationPReLU(INDArray alpha) {
this.alpha = alpha;
}
public ActivationPReLU(INDArray alpha, long[] sharedAxes) {
this.alpha = alpha;
this.sharedAxes = sharedAxes;
}
@Override
public INDArray getActivation(INDArray in, boolean training) {
DynamicCustomOp.DynamicCustomOpsBuilder prelu = DynamicCustomOp.builder("prelu")
.addOutputs(in).addInputs(in, alpha);
if (sharedAxes != null) {
for (long axis: sharedAxes) {
prelu.addIntegerArguments(axis);
}
}
Nd4j.getExecutioner().execAndReturn(prelu.build());
return in;
}
@Override
public Pair backprop(INDArray in, INDArray epsilon) {
assertShape(in, epsilon);
INDArray dLdalpha = Nd4j.create(alpha.shape());
DynamicCustomOp.DynamicCustomOpsBuilder preluBp = DynamicCustomOp.builder("prelu_bp")
.addInputs(in, alpha, epsilon).addOutputs(in, alpha);
if (sharedAxes != null) {
for (long axis: sharedAxes) {
preluBp.addIntegerArguments(axis);
}
}
Nd4j.getExecutioner().execAndReturn(preluBp.build());
return new Pair<>(in, dLdalpha);
}
@Override
public String toString() {
return "prelu";
}
}