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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.linalg.api.complex.IComplexNumber;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.BaseTransformOp;
import org.nd4j.linalg.api.ops.Op;
import org.nd4j.linalg.api.ops.TransformOp;
/**
* Rational Tanh Approximation elementwise function, as described at https://github.com/deeplearning4j/libnd4j/issues/351
*
* @author [email protected]
*/
public class RationalTanh extends BaseTransformOp {
public RationalTanh() {}
public RationalTanh(INDArray x, INDArray z) {
super(x, z);
}
public RationalTanh(INDArray x, INDArray z, long n) {
super(x, z, n);
}
public RationalTanh(INDArray x, INDArray y, INDArray z, long n) {
super(x, y, z, n);
}
public RationalTanh(INDArray x, INDArray y, INDArray z) {
super(x, y, z, x.lengthLong());
}
public RationalTanh(INDArray x) {
super(x);
}
@Override
public int opNum() {
return 53;
}
@Override
public String name() {
return "rational_tanh";
}
@Override
public IComplexNumber op(IComplexNumber origin, double other) {
return null;
}
@Override
public IComplexNumber op(IComplexNumber origin, float other) {
return null;
}
@Override
public IComplexNumber op(IComplexNumber origin, IComplexNumber other) {
return null;
}
@Override
public float op(float origin, float other) {
return 0;
}
@Override
public double op(double origin, double other) {
return 0;
}
@Override
public double op(double origin) {
return 0;
}
@Override
public float op(float origin) {
return 0;
}
@Override
public IComplexNumber op(IComplexNumber origin) {
return null;
}
@Override
public TransformOp derivative() {
return new RationalTanhDerivative(x, y, z, n);
}
@Override
public Op opForDimension(int index, int dimension) {
INDArray xAlongDimension = x.vectorAlongDimension(index, dimension);
if (y() != null)
return new RationalTanh(xAlongDimension, y.vectorAlongDimension(index, dimension),
z.vectorAlongDimension(index, dimension), xAlongDimension.length());
else
return new RationalTanh(xAlongDimension, z.vectorAlongDimension(index, dimension),
xAlongDimension.length());
}
@Override
public Op opForDimension(int index, int... dimension) {
INDArray xAlongDimension = x.tensorAlongDimension(index, dimension);
if (y() != null)
return new RationalTanh(xAlongDimension, y.tensorAlongDimension(index, dimension),
z.tensorAlongDimension(index, dimension), xAlongDimension.length());
else
return new RationalTanh(xAlongDimension, z.tensorAlongDimension(index, dimension),
xAlongDimension.length());
}
}