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/*
 *
 *  * Copyright 2016 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://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.
 *
 */
package org.deeplearning4j.arbiter.layers;

import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
import org.deeplearning4j.nn.conf.layers.BasePretrainNetwork;
import org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction;



public abstract class BasePretrainNetworkLayerSpace extends FeedForwardLayerSpace {

    protected ParameterSpace lossFunction;

    protected BasePretrainNetworkLayerSpace(Builder builder) {
        super(builder);
        this.lossFunction = builder.lossFunction;
    }


    public static abstract class Builder extends FeedForwardLayerSpace.Builder {
        protected ParameterSpace lossFunction;

        public T lossFunction(LossFunction lossFunction) {
            return lossFunction(new FixedValue(lossFunction));
        }

        public T lossFunction(ParameterSpace lossFunction) {
            this.lossFunction = lossFunction;
            return (T) this;
        }

    }

}