org.nd4j.linalg.api.ops.impl.transforms.strict.ACosh 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.api.ops.impl.transforms.strict;
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.BaseTransformFloatOp;
import org.nd4j.linalg.api.ops.BaseTransformOp;
import org.nd4j.linalg.api.ops.BaseTransformStrictOp;
import java.util.Arrays;
import java.util.List;
/**
* ACosh elementwise function
*
* @author Adam Gibson
*/
public class ACosh extends BaseTransformStrictOp {
public ACosh() {
}
public ACosh(INDArray x) {
super(x);
}
public ACosh(INDArray x, INDArray y) {
super(x, y);
}
public ACosh(SameDiff sameDiff, SDVariable i_v) {
this(sameDiff, i_v, false);
}
public ACosh(SameDiff sameDiff, SDVariable i_v, boolean inPlace) {
super(sameDiff, i_v, inPlace);
}
@Override
public int opNum() {
return 46;
}
@Override
public String opName() {
return "acosh";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
return "Acosh";
}
@Override
public List doDiff(List i_v) {
//dacosh(x)/dx = 1/(sqrt(x^2-1)) -- note that domain is x >= 1
SDVariable xSqPlus1 = sameDiff.math().square(arg()).sub(1.0);
SDVariable sqrt = sameDiff.math().sqrt(xSqPlus1);
return Arrays.asList(i_v.get(0).div(sqrt));
}
}