nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/transforms/custom/ATan2.java
/*
* ******************************************************************************
* *
* *
* * 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.
* *
* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
* * 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.custom;
import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.impl.transforms.BaseDynamicTransformOp;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import org.nd4j.linalg.ops.transforms.Transforms;
public class ATan2 extends BaseDynamicTransformOp {
public ATan2(SameDiff sameDiff, SDVariable y, SDVariable x) {
super(sameDiff, new SDVariable[] {y, x} ,false);
}
/**
* Note that the order of x and y match {@link Math#atan2(double, double)},
* and are reversed when compared to OldATan2.
* See {@link Transforms#atan2(INDArray, INDArray)}
*/
public ATan2(INDArray x, INDArray y) {
this(x,y,null);
}
/**
* Note that the order of x and y match {@link Math#atan2(double, double)},
* and are reversed when compared to OldATan2.
* See {@link Transforms#atan2(INDArray, INDArray)}
*/
public ATan2(INDArray x, INDArray y, INDArray z) {
super(new INDArray[]{x, y}, wrapOrNull(z));
}
public ATan2() {}
@Override
public String opName() {
return "tf_atan2";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
return "Atan2";
}
@Override
public List<SDVariable> doDiff(List<SDVariable> i_v) {
//Let z=atan2(r), with r=y/x
//dz/dr = 1/(r^2+1), dr/dy = 1/x, dr/dx = -y/x^2
SDVariable y = larg();
SDVariable x = rarg();
val xGrad = sameDiff.math.neg(y.div(x.pow(2).add(y.pow(2)))).mul(i_v.get(0));
val yGrad = x.div(x.pow(2).add(y.pow(2))).mul(i_v.get(0));
return Arrays.asList(yGrad, xGrad);
}
@Override
public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 2, "Expected exactly 2 input datatypes for %s, got %s", getClass(), dataTypes);
Preconditions.checkState(dataTypes.get(0) == dataTypes.get(1), "Input datatypes must be same type: got %s", dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}