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/*-
*
* * Copyright 2015 Skymind,Inc.
* *
* * 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.
*
*
*/
package org.nd4j.linalg.api.ops.impl.transforms;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.BaseTransformOp;
import java.util.List;
/**
* Rectified linear unit 6, i.e. min(max(input, cutoff), 6), where cutoff can be chosen.
*
* @author Max Pumperla
*/
public class Relu6 extends BaseTransformOp {
private double cutoff = 0.0;
public Relu6(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, double cutoff) {
super(sameDiff, i_v1, i_v2, inPlace);
this.cutoff = cutoff;
this.extraArgs = new Object[]{cutoff};
}
public Relu6(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs, double cutoff) {
super(sameDiff, i_v1, i_v2, extraArgs);
this.cutoff = cutoff;
this.extraArgs = new Object[]{cutoff};
}
public Relu6(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double cutoff) {
super(sameDiff, i_v, inPlace);
this.cutoff = cutoff;
this.extraArgs = new Object[]{cutoff};
}
public Relu6() {
this.extraArgs = new Object[]{cutoff};
}
public Relu6(INDArray x, INDArray z, double cutoff) {
super(x, z);
this.cutoff = cutoff;
init(x, y, z, n); //Need to re-init to properly set cutoff in extra args array
}
public Relu6(INDArray x, INDArray z, long n, double cutoff) {
super(x, z, n);
this.cutoff = cutoff;
init(x, y, z, n);
}
public Relu6(INDArray x, INDArray y, INDArray z, long n, double cutoff) {
super(x, y, z, n);
this.cutoff = cutoff;
init(x, y, z, n);
}
public Relu6(INDArray x, double cutoff) {
super(x);
this.cutoff = cutoff;
init(x, y, z, n);
}
public Relu6(INDArray x, INDArray z) {
super(x, z);
}
public Relu6(INDArray x, INDArray z, long n) {
super(x, z, n);
}
public Relu6(INDArray x, INDArray y, INDArray z, long n) {
super(x, y, z, n);
}
public Relu6(INDArray x, INDArray y, INDArray z) {
super(x, y, z, x.lengthLong());
}
public Relu6(INDArray x) {
super(x);
}
@Override
public void init(INDArray x, INDArray y, INDArray z, long n) {
super.init(x, y, z, n);
this.extraArgs = new Object[]{cutoff};
}
@Override
public int opNum() {
return 96;
}
@Override
public String opName() {
return "relu6";
}
@Override
public String onnxName() { throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
return "Relu6";
}
@Override
public List doDiff(List i_v) {
// TODO: implement
throw new UnsupportedOperationException();
}
}