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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.Arrays;
import java.util.List;
/**
* Element-wise exponential function minus 1, i.e. for each element x in a tensor computes the
* transformation exp(x) - 1.
*
* @author [email protected]
*/
public class Expm1 extends BaseTransformOp {
public Expm1(SameDiff sameDiff, SDVariable i_v, boolean inPlace) {
super(sameDiff, i_v, inPlace);
}
public Expm1(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs) {
super(sameDiff, i_v, shape, inPlace, extraArgs);
}
public Expm1(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs) {
super(sameDiff, i_v, extraArgs);
}
public Expm1() {
}
public Expm1(INDArray x, INDArray z) {
super(x, z);
}
public Expm1(INDArray x, INDArray z, long n) {
super(x, z, n);
}
public Expm1(INDArray x, INDArray y, INDArray z, long n) {
super(x, y, z, n);
}
public Expm1(INDArray x) {
super(x);
}
@Override
public int opNum() {
return 91;
}
@Override
public String opName() {
return "expm1";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
return "Expm1";
}
@Override
public List doDiff(List i_v) {
SDVariable ret = f().mul(f().exp(arg()), i_v.get(0));
return Arrays.asList(ret);
}
}