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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.arbiter.util.CollectionUtils;
import org.deeplearning4j.nn.conf.layers.ConvolutionLayer;
import org.nd4j.linalg.convolution.Convolution;

import java.util.List;

/**
 * Layer space for convolutional layers
 *
 * @author Alex Black
 */
public class ConvolutionLayerSpace extends FeedForwardLayerSpace {

    protected ParameterSpace convolutionType;
    protected ParameterSpace kernelSize;
    protected ParameterSpace stride;
    protected ParameterSpace padding;

    private ConvolutionLayerSpace(Builder builder) {
        super(builder);
        this.convolutionType = builder.convolutionType;
        this.kernelSize = builder.kernelSize;
        this.stride = builder.stride;
        this.padding = builder.padding;

        this.numParameters = CollectionUtils.countUnique(collectLeaves());
    }

    @Override
    public List collectLeaves() {
        List list = super.collectLeaves();
        if (kernelSize != null) list.addAll(kernelSize.collectLeaves());
        if (stride != null) list.addAll(stride.collectLeaves());
        if (padding != null) list.addAll(padding.collectLeaves());
        return list;
    }

    @Override
    public ConvolutionLayer getValue(double[] values) {
        ConvolutionLayer.Builder b = new ConvolutionLayer.Builder();
        setLayerOptionsBuilder(b, values);
        return b.build();
    }

    protected void setLayerOptionsBuilder(ConvolutionLayer.Builder builder, double[] values) {
        super.setLayerOptionsBuilder(builder, values);
        if (convolutionType != null) builder.convolutionType(convolutionType.getValue(values));
        if (kernelSize != null) builder.kernelSize(kernelSize.getValue(values));
        if (stride != null) builder.stride(stride.getValue(values));
        if (padding != null) builder.padding(padding.getValue(values));
    }

    @Override
    public String toString() {
        return toString(", ");
    }

    @Override
    public String toString(String delim) {
        StringBuilder sb = new StringBuilder("ConvolutionLayerSpace(");
        if (convolutionType != null) sb.append("poolingType: ").append(convolutionType).append(delim);
        if (kernelSize != null) sb.append("kernelSize: ").append(kernelSize).append(delim);
        if (stride != null) sb.append("stride: ").append(stride).append(delim);
        if (padding != null) sb.append("padding: ").append(padding).append(delim);
        sb.append(super.toString(delim)).append(")");
        return sb.toString();
    }


    public static class Builder extends FeedForwardLayerSpace.Builder {

        protected ParameterSpace convolutionType;
        protected ParameterSpace kernelSize;
        protected ParameterSpace stride;
        protected ParameterSpace padding;

        public Builder convolutionType(Convolution.Type convolutionType) {
            return convolutionType(new FixedValue<>(convolutionType));
        }

        public Builder convolutionType(ParameterSpace convolutionType) {
            this.convolutionType = convolutionType;
            return this;
        }

        public Builder kernelSize(int... kernelSize) {
            return kernelSize(new FixedValue<>(kernelSize));
        }

        public Builder kernelSize(ParameterSpace kernelSize) {
            this.kernelSize = kernelSize;
            return this;
        }

        public Builder stride(int... stride) {
            return stride(new FixedValue<>(stride));
        }

        public Builder stride(ParameterSpace stride) {
            this.stride = stride;
            return this;
        }

        public Builder padding(int... padding) {
            return padding(new FixedValue<>(padding));
        }

        public Builder padding(ParameterSpace padding) {
            this.padding = padding;
            return this;
        }

        public ConvolutionLayerSpace build() {
            return new ConvolutionLayerSpace(this);
        }

    }

}