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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.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.BaseTransformOp;
import java.util.Arrays;
import java.util.List;
/**
* Softsign element-wise activation function. f(x) = x/(1+abs(x))
* Similar in shape to tanh but may outperform it due to
* 'gentler' nonlinearity (smoother asymptotes).
* See for example: http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf
*
* @author Alex Black
*/
public class SoftSign extends BaseTransformOp {
public SoftSign(SameDiff sameDiff, SDVariable i_v, boolean inPlace) {
super(sameDiff, i_v, inPlace);
}
public SoftSign(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs) {
super(sameDiff, i_v, shape, inPlace, extraArgs);
}
public SoftSign(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs) {
super(sameDiff, i_v, extraArgs);
}
public SoftSign() {
}
public SoftSign(INDArray x, INDArray z) {
super(x, z);
}
public SoftSign(INDArray x, INDArray z, long n) {
super(x, z, n);
}
public SoftSign(INDArray x, INDArray y, INDArray z, long n) {
super(x, y, z, n);
}
public SoftSign(INDArray x) {
super(x);
}
@Override
public int opNum() {
return 20;
}
@Override
public String opName() {
return "softsign";
}
@Override
public String onnxName() {
return "Softsign";
}
@Override
public String tensorflowName() {
return "Softsign";
}
@Override
public List doDiff(List i_v) {
SDVariable ret = f().softsignDerivative(arg()).mul(i_v.get(0));
return Arrays.asList(ret);
}
}