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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.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.Collections;
import java.util.List;
/**
* Unit step function.
* f(x) = 1 if x > cutoff; 0 otherwise
* cutoff = 0.0 usually.
*/
public class Step extends BaseTransformOp {
private final double cutoff;
public Step(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double cutoff) {
super(sameDiff, i_v, inPlace);
this.cutoff = cutoff;
this.extraArgs = new Object[] {cutoff};
}
public Step(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs, double cutoff) {
super(sameDiff, i_v, shape, inPlace, extraArgs);
this.cutoff = cutoff;
this.extraArgs = new Object[] {cutoff};
}
public Step(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double cutoff) {
super(sameDiff, i_v, extraArgs);
this.cutoff = cutoff;
this.extraArgs = new Object[] {cutoff};
}
public Step() {
cutoff = 0.0;
this.extraArgs = new Object[] {cutoff};
}
public Step(INDArray x, INDArray z) {
super(x, z);
cutoff = 0.0;
this.extraArgs = new Object[] {cutoff};
}
public Step(INDArray x, INDArray z, long n) {
super(x, z, n);
cutoff = 0.0;
this.extraArgs = new Object[] {cutoff};
}
public Step(INDArray x, INDArray y, INDArray z, long n) {
super(x, y, z, n);
cutoff = 0.0;
this.extraArgs = new Object[] {cutoff};
}
public Step(INDArray x) {
super(x);
cutoff = 0.0;
this.extraArgs = new Object[] {cutoff};
}
public Step(INDArray x, INDArray z, double cutoff) {
super(x, z);
this.cutoff = cutoff;
this.extraArgs = new Object[] {cutoff};
}
public Step(INDArray x, INDArray z, long n, double cutoff) {
super(x, z, n);
this.cutoff = cutoff;
this.extraArgs = new Object[] {cutoff};
}
public Step(INDArray x, INDArray y, INDArray z, long n, double cutoff) {
super(x, y, z, n);
this.cutoff = cutoff;
this.extraArgs = new Object[] {cutoff};
}
public Step(INDArray x, double cutoff) {
super(x);
this.cutoff = cutoff;
this.extraArgs = new Object[] {cutoff};
}
@Override
public int opNum() {
return 34;
}
@Override
public String opName() {
return "step";
}
@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 void init(INDArray x, INDArray y, INDArray z, long n) {
super.init(x, y, z, n);
this.extraArgs = new Object[] {cutoff};
}
@Override
public List doDiff(List f1) {
return Collections.singletonList(f().zerosLike(arg()));
}
}