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/*
 *  ******************************************************************************
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 *  * 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.
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 *  * SPDX-License-Identifier: Apache-2.0
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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 Erfc extends BaseTransformStrictOp {

    public Erfc(SameDiff sameDiff, SDVariable i_v){
        this(sameDiff, i_v, false);
    }

    public Erfc(SameDiff sameDiff, SDVariable i_v, boolean inPlace) {
        super(sameDiff, i_v, inPlace);
    }

    public Erfc(INDArray x, INDArray z) {
        super(x, z);
    }

    public Erfc(INDArray x) {
        super(x);
    }

    @Override
    public int opNum() {
        return 50;
    }

    @Override
    public String opName() {
        return "erfc";
    }

    @Override
    public String onnxName() {
        throw new NoOpNameFoundException("No onnx op opName found for " + opName());
    }

    @Override
    public String tensorflowName() {
        return "Erfc";
    }


    @Override
    public List doDiff(List i_v) {
        // erfc(z) = 1 - erf(z)
        // Derivative of erf(z) is 2 / sqrt(pi) * e^(-z^2), so have to multiply by -1.
        SDVariable gradient = i_v.get(0);
        SDVariable z = arg();
        SDVariable constant = sameDiff.onesLike(gradient).mul(-2.0 / Math.sqrt(Math.PI));
        SDVariable ret = constant.mul(sameDiff.math().exp(z.mul(z).mul(-1))).mul(gradient);
        return Collections.singletonList(ret);
    }
}