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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.accum;

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.BaseAccumulation;

import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;

/**
 * Calculate a bias
 *
 * @author Adam Gibson
 */
public class Bias extends BaseAccumulation {

    private double mean;

    public Bias(SameDiff sameDiff, SDVariable i_v, int[] dimensions, double mean) {
        super(sameDiff, i_v, dimensions);
        this.mean = mean;
    }

    public Bias(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, double mean) {
        super(sameDiff, i_v, i_v2, dimensions);
        this.mean = mean;
    }

    public Bias() {}

    public Bias(INDArray x, INDArray y, INDArray z, long n) {
        super(x, y, z, n);
    }

    public Bias(INDArray x, INDArray y, long n) {
        this(x, y, x, n);
    }

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

    public Bias(INDArray x, INDArray y) {
        super(x, y);
    }

    @Override
    public Map propertiesForFunction() {
        Map ret = new LinkedHashMap<>();
        ret.put("mean",mean);
        return ret;
    }

    @Override
    public int opNum() {
        return 2;
    }

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


    @Override
    public boolean isPassThrough() {
        return false;
    }


    @Override
    public List doDiff(List f1) {
        return null;
    }

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

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

    @Override
    public Type getOpType() {
        return Type.REDUCE;
    }
}