org.nd4j.linalg.api.ops.impl.transforms.strict.ATan Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
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* * information regarding copyright ownership.
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package org.nd4j.linalg.api.ops.impl.transforms.strict;
import lombok.NoArgsConstructor;
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.BaseTransformStrictOp;
import java.util.Collections;
import java.util.List;
@NoArgsConstructor
public class ATan extends BaseTransformStrictOp {
public ATan(SameDiff sameDiff, SDVariable i_v, boolean inPlace) {
super(sameDiff, i_v, inPlace);
}
public ATan(SameDiff sameDiff, SDVariable i_v) {
this(sameDiff, i_v, false);
}
public ATan(INDArray x, INDArray z) {
super(x, z);
}
public ATan(INDArray x) {
super(x);
}
@Override
public int opNum() {
return 32;
}
@Override
public String opName() {
return "atan";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
return "Atan";
}
@Override
public List doDiff(List i_v) {
//d(atan(x))/dx = 1/(x^2+1)
SDVariable xSqPlus1 = sameDiff.math.square(arg()).add(1.0);
SDVariable ret = xSqPlus1.rdiv(1.0).mul(i_v.get(0));
return Collections.singletonList(ret);
}
}