org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer Maven / Gradle / Ivy

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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.
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 *  *  information regarding copyright ownership.
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package org.deeplearning4j.nn.conf.layers;

import lombok.*;
import org.deeplearning4j.nn.api.ParamInitializer;
import org.deeplearning4j.nn.conf.CNN2DFormat;
import org.deeplearning4j.nn.conf.InputPreProcessor;
import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
import org.deeplearning4j.nn.conf.inputs.InputType;
import org.deeplearning4j.nn.conf.memory.LayerMemoryReport;
import org.deeplearning4j.nn.conf.memory.MemoryReport;
import org.deeplearning4j.nn.params.EmptyParamInitializer;
import org.deeplearning4j.optimize.api.TrainingListener;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;

import java.util.Collection;
import java.util.Map;

@Data
@NoArgsConstructor
@ToString(callSuper = true)
@EqualsAndHashCode(callSuper = true)
public class SpaceToDepthLayer extends NoParamLayer {

    /**
     * @deprecated Use {@link CNN2DFormat} instead
     */
    @Deprecated
    public enum DataFormat {
        NCHW, NHWC;

        public CNN2DFormat toFormat(){
            return this == NCHW ? CNN2DFormat.NCHW : CNN2DFormat.NHWC;
        }
    }

    protected int blockSize;
    protected CNN2DFormat dataFormat;


    protected SpaceToDepthLayer(Builder builder) {
        super(builder);
        this.setBlockSize(builder.blockSize);
        this.setDataFormat(builder.dataFormat);
    }

    @Override
    public SpaceToDepthLayer clone() {
        return (SpaceToDepthLayer) super.clone();
    }

    @Override
    public org.deeplearning4j.nn.api.Layer instantiate(NeuralNetConfiguration conf,
                                                       Collection trainingListeners, int layerIndex, INDArray layerParamsView,
                                                       boolean initializeParams, DataType networkDataType) {
        org.deeplearning4j.nn.layers.convolution.SpaceToDepth ret =
                        new org.deeplearning4j.nn.layers.convolution.SpaceToDepth(conf, networkDataType);
        ret.setListeners(trainingListeners);
        ret.setIndex(layerIndex);
        ret.setParamsViewArray(layerParamsView);
        Map paramTable = initializer().init(conf, layerParamsView, initializeParams);
        ret.setParamTable(paramTable);
        ret.setConf(conf);
        return ret;
    }

    @Override
    public LayerMemoryReport getMemoryReport(InputType inputType) {
        InputType.InputTypeConvolutional outputType = (InputType.InputTypeConvolutional) getOutputType(-1, inputType);

        return new LayerMemoryReport.Builder(layerName, SpaceToDepthLayer.class, inputType, outputType)
                        .standardMemory(0, 0) //No params
                        .cacheMemory(MemoryReport.CACHE_MODE_ALL_ZEROS, MemoryReport.CACHE_MODE_ALL_ZEROS) //No caching
                        .build();
    }

    @Override
    public InputType getOutputType(int layerIndex, InputType inputType) {
        if (inputType == null || inputType.getType() != InputType.Type.CNN) {
            throw new IllegalStateException("Invalid input for space to channels layer (layer name=\"" + getLayerName()
                            + "\"): Expected CNN input, got " + inputType);
        }
        InputType.InputTypeConvolutional i = (InputType.InputTypeConvolutional) inputType;
        return InputType.convolutional(i.getHeight() / blockSize, i.getWidth() / blockSize,
                        i.getChannels() * blockSize * blockSize, i.getFormat());
    }

    @Override
    public ParamInitializer initializer() {
        return EmptyParamInitializer.getInstance();
    }


    @Override
    public void setNIn(InputType inputType, boolean override) {
        this.dataFormat = ((InputType.InputTypeConvolutional)inputType).getFormat();
    }

    @Override
    public InputPreProcessor getPreProcessorForInputType(InputType inputType) {
        if (inputType == null) {
            throw new IllegalStateException("Invalid input for space to channels layer (layer name=\"" + getLayerName()
                            + "\"): input is null");
        }
        return InputTypeUtil.getPreProcessorForInputTypeCnnLayers(inputType, getLayerName());
    }

    @Override
    public boolean isPretrainParam(String paramName) {
        throw new UnsupportedOperationException("SpaceToDepthLayer does not contain parameters");
    }


    @NoArgsConstructor
    @Getter
    @Setter
    public static class Builder> extends Layer.Builder {

        protected int blockSize;

        /**
         * Data format for input activations. Note DL4J uses NCHW in most cases
         */
        protected CNN2DFormat dataFormat = CNN2DFormat.NCHW;

        /**
         * @param blockSize Block size
         */
        public Builder(int blockSize) {
            this.setBlockSize(blockSize);
        }

        /**
         * @param blockSize Block size
         * @param dataFormat Data format for input activations. Note DL4J uses NCHW in most cases
         */
        @Deprecated
        public Builder(int blockSize, DataFormat dataFormat) {
            this(blockSize, dataFormat.toFormat());
        }

        public Builder(int blockSize, CNN2DFormat dataFormat) {
            this.setBlockSize(blockSize);
            this.setDataFormat(dataFormat);
        }

        /**
         * @param blockSize Block size
         */
        public T blocks(int blockSize) {
            this.setBlockSize(blockSize);
            return (T) this;
        }

        /**
         * @param dataFormat Data format for input activations. Note DL4J uses NCHW in most cases
         * @deprecated Use {@link #dataFormat(CNN2DFormat)}
         */
        @Deprecated
        public T dataFormat(DataFormat dataFormat) {
            return dataFormat(dataFormat.toFormat());
        }

        /**
         * Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
         * See {@link CNN2DFormat} for more details.

         * Default: NCHW
         * @param dataFormat Format for activations (in and out)
         */
        public T dataFormat(CNN2DFormat dataFormat) {
            this.setDataFormat(dataFormat);
            return (T) this;
        }

        @Override
        public T name(String layerName) {
            this.setLayerName(layerName);
            return (T) this;
        }

        @Override
        @SuppressWarnings("unchecked")
        public SpaceToDepthLayer build() {
            return new SpaceToDepthLayer(this);
        }
    }

}