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Java example source code file (InputPreProcessor.java)

This example Java source code file (InputPreProcessor.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.

Learn more about this Java project at its project page.

Java - Java tags/keywords

cloneable, indarray, inputpreprocessor, jsonsubtypes, jsontypeinfo, serializable

The InputPreProcessor.java Java example source code

/*
 *
 *  * Copyright 2015 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;


import com.fasterxml.jackson.annotation.JsonSubTypes;
import com.fasterxml.jackson.annotation.JsonTypeInfo;

import org.deeplearning4j.nn.api.Layer;
import org.deeplearning4j.nn.conf.preprocessor.*;
import org.nd4j.linalg.api.ndarray.INDArray;

import java.io.Serializable;

/**
 * Input pre processor used
 * for pre processing input before passing it
 * to the neural network.
 *
 * @author Adam Gibson
 */
@JsonTypeInfo(use= JsonTypeInfo.Id.NAME, include= JsonTypeInfo.As.WRAPPER_OBJECT)
@JsonSubTypes(value={
        @JsonSubTypes.Type(value = CnnToFeedForwardPreProcessor.class, name = "cnnToFeedForward"),
        @JsonSubTypes.Type(value = CnnToRnnPreProcessor.class, name = "cnnToRnn"),
        @JsonSubTypes.Type(value = ComposableInputPreProcessor.class, name = "composableInput"),
        @JsonSubTypes.Type(value = FeedForwardToCnnPreProcessor.class, name = "feedForwardToCnn"),
        @JsonSubTypes.Type(value = FeedForwardToRnnPreProcessor.class, name = "feedForwardToRnn"),
        @JsonSubTypes.Type(value = RnnToFeedForwardPreProcessor.class, name = "rnnToFeedForward"),
        @JsonSubTypes.Type(value = RnnToCnnPreProcessor.class, name = "rnnToCnn"),
        @JsonSubTypes.Type(value = BinomialSamplingPreProcessor.class, name = "binomialSampling"),
        @JsonSubTypes.Type(value = ReshapePreProcessor.class, name = "reshape"),
        @JsonSubTypes.Type(value = UnitVarianceProcessor.class, name = "unitVariance"),
        @JsonSubTypes.Type(value = ZeroMeanAndUnitVariancePreProcessor.class, name = "zeroMeanAndUnitVariance"),
        @JsonSubTypes.Type(value = ZeroMeanPrePreProcessor.class, name = "zeroMean"),
})
public interface InputPreProcessor extends Serializable, Cloneable {


    /**
     * Pre preProcess input/activations for a multi layer network
     * @param input the input to pre preProcess
     * @param miniBatchSize
     * @return the processed input
     */
    INDArray preProcess(INDArray input, int miniBatchSize);

    /**Reverse the preProcess during backprop. Process Gradient/epsilons before
     * passing them to the layer below.
     * @param output which is a pair of the gradient and epsilon
     * @param miniBatchSize
     * @return the reverse of the pre preProcess step (if any)
     */
    INDArray backprop(INDArray output, int miniBatchSize);

    InputPreProcessor clone();
}

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