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Java example source code file (InputType.java)

This example Java source code file (InputType.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

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Java - Java tags/keywords

allargsconstructor, cnn, data, equalsandhashcode, getter, inputtype, inputtypeconvolutional, inputtypefeedforward, inputtyperecurrent, override, rnn, serializable, type

The InputType.java Java example source code

/*
 *
 *  * 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.nn.conf.inputs;

import lombok.*;

import java.io.Serializable;

/** The InputType class is used to track and define the types of activations etc used in a ComputationGraph.
 * This is most useful for automatically adding preprocessors between layers.
 * See: {@link org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder#setInputTypes(InputType...)} and
 * {@link org.deeplearning4j.nn.conf.ComputationGraphConfiguration#addPreProcessors(InputType...)}
 * @author Alex Black
 */
public abstract class InputType implements Serializable {

    /** The type of activations in/out of a given GraphVertex. */
    public enum Type {FF, RNN, CNN};


    public abstract Type getType();

    /** InputType for feed forward network data
     * @param size The size of the activations
     */
    public static InputType feedForward(int size){
        return new InputTypeFeedForward(size);
    }

    /** InputType for recurrent neural network (time series) data
     * @param size The size of the activations
     * @return
     */
    public static InputType recurrent(int size){
        return new InputTypeRecurrent(size);
    }

    /**Input type for convolutional (CNN) data
     * @param height height of the input
     * @param width Width of the input
     * @param depth Depth, or number of channels
     * @return
     */
    public static InputType convolutional(int height, int width, int depth){
        return new InputTypeConvolutional(height,width,depth);
    }


    @AllArgsConstructor @Getter
    public static class InputTypeFeedForward extends InputType{
        private int size;

        @Override
        public Type getType() {
            return Type.FF;
        }
    }

    @AllArgsConstructor @Getter
    public static class InputTypeRecurrent extends InputType{
        private int size;

        @Override
        public Type getType() {
            return Type.RNN;
        }
    }

    @AllArgsConstructor @Data  @EqualsAndHashCode(callSuper=false)
    public static class InputTypeConvolutional extends InputType {
        private int height;
        private int width;
        private int depth;

        @Override
        public Type getType() {
            return Type.CNN;
        }
    }


}

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