com.simiacryptus.mindseye.layers.cudnn.conv.FullyConnectedLayer.java Source code

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/*
 * Copyright (c) 2018 by Andrew Charneski.
 *
 * The author licenses this file to you 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 com.simiacryptus.mindseye.layers.cudnn.conv;

import com.google.gson.JsonObject;
import com.simiacryptus.mindseye.lang.*;
import com.simiacryptus.mindseye.lang.cudnn.CudaSystem;
import com.simiacryptus.mindseye.lang.cudnn.MultiPrecision;
import com.simiacryptus.mindseye.lang.cudnn.Precision;
import com.simiacryptus.mindseye.layers.Explodable;
import com.simiacryptus.mindseye.layers.java.FullyConnectedReferenceLayer;
import com.simiacryptus.mindseye.layers.java.ReshapeLayer;
import com.simiacryptus.mindseye.network.PipelineNetwork;
import com.simiacryptus.util.FastRandom;
import com.simiacryptus.util.JsonUtil;
import com.simiacryptus.util.Util;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import javax.annotation.Nonnull;
import javax.annotation.Nullable;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
import java.util.function.DoubleSupplier;

/**
 * A dense matrix operator using vector-matrix multiplication. Represents a fully connected key of synapses, where all
 * inputs are connected to all outputs via seperate coefficients.
 */
@SuppressWarnings("serial")
public class FullyConnectedLayer extends LayerBase implements MultiPrecision<FullyConnectedLayer>, Explodable {
    private static final Logger log = LoggerFactory.getLogger(FullyConnectedLayer.class);
    /**
     * The Input dims.
     */
    @Nullable
    public final int[] inputDims;
    /**
     * The Output dims.
     */
    @Nullable
    public final int[] outputDims;
    @Nullable
    private final Tensor weights;

    private Precision precision = Precision.Double;
    private int batchBands = 0;

    /**
     * Instantiates a new Img eval key.
     */
    private FullyConnectedLayer() {
        outputDims = null;
        weights = null;
        inputDims = null;
    }

    /**
     * Instantiates a new Fully connected key.
     *
     * @param inputDims  the input dims
     * @param outputDims the output dims
     */
    public FullyConnectedLayer(@Nonnull final int[] inputDims, @Nonnull final int[] outputDims) {
        final int inputs = Tensor.length(inputDims);
        this.inputDims = Arrays.copyOf(inputDims, inputDims.length);
        this.outputDims = Arrays.copyOf(outputDims, outputDims.length);
        final int outs = Tensor.length(outputDims);
        weights = new Tensor(inputs, outs);
        setWeights(() -> {
            final double ratio = Math.sqrt(6. / (inputs + outs + 1));
            final double fate = Util.R.get().nextDouble();
            final double v = (1 - 2 * fate) * ratio;
            return v;
        });
    }

    /**
     * Instantiates a new Img eval key.
     *
     * @param json the json
     * @param rs   the rs
     */
    protected FullyConnectedLayer(@Nonnull final JsonObject json, Map<CharSequence, byte[]> rs) {
        super(json);
        outputDims = JsonUtil.getIntArray(json.getAsJsonArray("outputDims"));
        inputDims = JsonUtil.getIntArray(json.getAsJsonArray("inputDims"));
        @Nullable
        final Tensor data = Tensor.fromJson(json.get("weights"), rs);
        weights = data;
        this.precision = Precision.valueOf(json.getAsJsonPrimitive("precision").getAsString());
    }

    /**
     * From json img eval key.
     *
     * @param json the json
     * @param rs   the rs
     * @return the img eval key
     */
    public static FullyConnectedLayer fromJson(@Nonnull final JsonObject json, Map<CharSequence, byte[]> rs) {
        return new FullyConnectedLayer(json, rs);
    }

    /**
     * Sets weights.
     *
     * @param data the data
     * @return the weights
     */
    @Nonnull
    public FullyConnectedLayer set(final double[] data) {
        weights.set(data);
        return this;
    }

    /**
     * Set fully connected key.
     *
     * @param data the data
     * @return the fully connected key
     */
    @Nonnull
    public FullyConnectedLayer set(@Nonnull final Tensor data) {
        weights.set(data);
        return this;
    }

    /**
     * Sets weights log.
     *
     * @param value the value
     * @return the weights log
     */
    @Nonnull
    public FullyConnectedLayer setWeightsLog(final double value) {
        getWeights().setByCoord(c -> (FastRandom.INSTANCE.random() - 0.5) * Math.pow(10, value));
        return this;
    }

    /**
     * Gets compatibility key.
     *
     * @return the compatibility key
     */
    @Nonnull
    public Layer getCompatibilityLayer() {
        return new FullyConnectedReferenceLayer(inputDims, outputDims).set(getWeights());
    }

    @Nullable
    @Override
    public Result evalAndFree(final Result... inObj) {
        if (!CudaSystem.isEnabled())
            return getCompatibilityLayer().evalAndFree(inObj);
        Layer explode = explode();
        Result eval = explode.evalAndFree(inObj);
        explode.freeRef();
        return eval;
    }

    /**
     * Explode pipeline network.
     *
     * @return the pipeline network
     */
    @Nonnull
    public Layer explode() {
        int inputVol = Tensor.length(inputDims);
        int outVol = Tensor.length(outputDims);
        @Nonnull
        PipelineNetwork network = new PipelineNetwork(1);
        network.wrap(new ReshapeLayer(1, 1, inputVol)).freeRef();
        @Nullable
        Tensor tensor = this.weights.reshapeCast(1, 1, inputVol * outVol);
        @Nonnull
        ConvolutionLayer convolutionLayer = new ConvolutionLayer(1, 1, inputVol, outVol).set(tensor)
                .setBatchBands(getBatchBands());
        @Nonnull
        ExplodedConvolutionGrid grid = convolutionLayer.getExplodedNetwork();
        convolutionLayer.freeRef();
        tensor.freeRef();
        grid.add(network.getHead());
        grid.freeRef();
        network.wrap(new ReshapeLayer(outputDims)).freeRef();
        network.setName(getName());
        return network;
    }

    @Nonnull
    @Override
    public JsonObject getJson(Map<CharSequence, byte[]> resources, @Nonnull DataSerializer dataSerializer) {
        @Nonnull
        final JsonObject json = super.getJsonStub();
        json.add("outputDims", JsonUtil.getJson(outputDims));
        json.add("inputDims", JsonUtil.getJson(inputDims));
        @Nullable
        Tensor tensor = getWeights();
        json.add("weights", tensor.toJson(resources, dataSerializer));
        json.addProperty("precision", precision.name());
        return json;
    }

    @Nonnull
    @Override
    public List<double[]> state() {
        return Arrays.asList(getWeights().getData());
    }

    @Override
    public Precision getPrecision() {
        return precision;
    }

    @Nonnull
    @Override
    public FullyConnectedLayer setPrecision(final Precision precision) {
        this.precision = precision;
        return this;
    }

    /**
     * The Weights.
     *
     * @return the weights
     */
    @Nullable
    public Tensor getWeights() {
        return weights;
    }

    /**
     * Sets weights.
     *
     * @param f the f
     * @return the weights
     */
    @Nonnull
    public FullyConnectedLayer setWeights(@Nonnull final DoubleSupplier f) {
        Arrays.parallelSetAll(getWeights().getData(), i -> f.getAsDouble());
        return this;
    }

    /**
     * Gets batch bands.
     *
     * @return the batch bands
     */
    public int getBatchBands() {
        return batchBands;
    }

    /**
     * Sets batch bands.
     *
     * @param batchBands the batch bands
     * @return the batch bands
     */
    @Nonnull
    public FullyConnectedLayer setBatchBands(int batchBands) {
        this.batchBands = batchBands;
        return this;
    }
}