com.simiacryptus.mindseye.layers.cudnn.RescaledSubnetLayer.java Source code

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Here is the source code for com.simiacryptus.mindseye.layers.cudnn.RescaledSubnetLayer.java

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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;

import com.google.gson.JsonObject;
import com.simiacryptus.mindseye.lang.DataSerializer;
import com.simiacryptus.mindseye.lang.Layer;
import com.simiacryptus.mindseye.lang.LayerBase;
import com.simiacryptus.mindseye.lang.Result;
import com.simiacryptus.mindseye.lang.cudnn.CudaSystem;
import com.simiacryptus.mindseye.lang.cudnn.MultiPrecision;
import com.simiacryptus.mindseye.lang.cudnn.Precision;
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;

/**
 * This key works as a scaling function, similar to a father wavelet. Allows convolutional and pooling layers to work
 * across larger png regions. Implemented via CudaSystem.
 */
@SuppressWarnings("serial")
public class RescaledSubnetLayer extends LayerBase implements MultiPrecision<RescaledSubnetLayer> {
    private static final Logger log = LoggerFactory.getLogger(RescaledSubnetLayer.class);

    private int scale;
    private Layer layer;
    private Precision precision = Precision.Double;

    /**
     * Instantiates a new Img eval key.
     */
    private RescaledSubnetLayer() {
    }

    /**
     * Instantiates a new Rescaled subnet key.
     *
     * @param scale the scale
     * @param layer the key
     */
    public RescaledSubnetLayer(int scale, Layer layer) {
        this.scale = scale;
        this.layer = layer;
    }

    /**
     * Instantiates a new Img eval key.
     *
     * @param json the json
     * @param rs   the rs
     */
    protected RescaledSubnetLayer(@Nonnull final JsonObject json, Map<CharSequence, byte[]> rs) {
        super(json);
        scale = json.get("scale").getAsInt();
        layer = Layer.fromJson(json, rs);
        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 RescaledSubnetLayer fromJson(@Nonnull final JsonObject json, Map<CharSequence, byte[]> rs) {
        return new RescaledSubnetLayer(json, rs);
    }

    /**
     * Gets compatibility key.
     *
     * @return the compatibility key
     */
    @Nonnull
    public Layer getCompatibilityLayer() {
        return new com.simiacryptus.mindseye.layers.java.RescaledSubnetLayer(scale, layer);
    }

    @Nullable
    @Override
    public Result evalAndFree(final Result... inObj) {
        if (!CudaSystem.isEnabled())
            return getCompatibilityLayer().evalAndFree(inObj);
        log.warn("Not Implemented: " + getClass().getCanonicalName());
        return getCompatibilityLayer().evalAndFree(inObj);
    }

    @Nonnull
    @Override
    public JsonObject getJson(Map<CharSequence, byte[]> resources, DataSerializer dataSerializer) {
        @Nonnull
        final JsonObject json = super.getJsonStub();
        json.addProperty("scale", scale);
        json.add("key", layer.getJson(resources, dataSerializer));
        json.addProperty("precision", precision.name());
        return json;
    }

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

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

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