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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
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package org.deeplearning4j.nn.weights;

import lombok.EqualsAndHashCode;
import org.apache.commons.math3.util.FastMath;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;

/**
 * Normal/Gaussian distribution, with mean 0 and standard deviation 1/sqrt(fanIn).
 *
 * @author Adam Gibson
 */
@EqualsAndHashCode
public class WeightInitNormal implements IWeightInit {

    @Override
    public INDArray init(double fanIn, double fanOut, long[] shape, char order, INDArray paramView) {
        Nd4j.randn(paramView).divi(FastMath.sqrt(fanIn));
        return paramView.reshape(order, shape);
    }
}




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