com.simiacryptus.mindseye.layers.java.ImgBandScaleLayer.java Source code

Java tutorial

Introduction

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

Source

/*
 * 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.java;

import com.google.gson.JsonObject;
import com.simiacryptus.mindseye.lang.*;
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.UUID;
import java.util.function.DoubleSupplier;
import java.util.function.Function;
import java.util.function.IntToDoubleFunction;
import java.util.stream.IntStream;

/**
 * Scales the input using per-color-band coefficients
 */
@SuppressWarnings("serial")
public class ImgBandScaleLayer extends LayerBase {

    @SuppressWarnings("unused")
    private static final Logger log = LoggerFactory.getLogger(ImgBandScaleLayer.class);
    @Nullable
    private final double[] weights;

    /**
     * Instantiates a new Img band scale key.
     */
    protected ImgBandScaleLayer() {
        super();
        weights = null;
    }

    /**
     * Instantiates a new Img band scale key.
     *
     * @param bands the bands
     */
    public ImgBandScaleLayer(final double... bands) {
        super();
        weights = bands;
    }

    /**
     * Instantiates a new Img band scale key.
     *
     * @param json the json
     */
    protected ImgBandScaleLayer(@Nonnull final JsonObject json) {
        super(json);
        weights = JsonUtil.getDoubleArray(json.getAsJsonArray("bias"));
    }

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

    /**
     * Add weights img band scale key.
     *
     * @param f the f
     * @return the img band scale key
     */
    @Nonnull
    public ImgBandScaleLayer addWeights(@Nonnull final DoubleSupplier f) {
        Util.add(f, getWeights());
        return this;
    }

    @Nonnull
    @Override
    public Result eval(final Result... inObj) {
        return eval(inObj[0]);
    }

    /**
     * Eval nn result.
     *
     * @param input the input
     * @return the nn result
     */
    @Nonnull
    public Result eval(@Nonnull final Result input) {
        @Nullable
        final double[] weights = getWeights();
        final TensorList inData = input.getData();
        inData.addRef();
        input.addRef();
        @Nullable
        Function<Tensor, Tensor> tensorTensorFunction = tensor -> {
            if (tensor.getDimensions().length != 3) {
                throw new IllegalArgumentException(Arrays.toString(tensor.getDimensions()));
            }
            if (tensor.getDimensions()[2] != weights.length) {
                throw new IllegalArgumentException(String.format("%s: %s does not have %s bands", getName(),
                        Arrays.toString(tensor.getDimensions()), weights.length));
            }
            @Nullable
            Tensor tensor1 = tensor.mapCoords(c -> tensor.get(c) * weights[c.getCoords()[2]]);
            tensor.freeRef();
            return tensor1;
        };
        Tensor[] data = inData.stream().parallel().map(tensorTensorFunction).toArray(i -> new Tensor[i]);
        return new Result(TensorArray.wrap(data),
                (@Nonnull final DeltaSet<UUID> buffer, @Nonnull final TensorList delta) -> {
                    if (!isFrozen()) {
                        final Delta<UUID> deltaBuffer = buffer.get(ImgBandScaleLayer.this.getId(), weights);
                        IntStream.range(0, delta.length()).forEach(index -> {
                            @Nonnull
                            int[] dimensions = delta.getDimensions();
                            int z = dimensions[2];
                            int y = dimensions[1];
                            int x = dimensions[0];
                            final double[] array = RecycleBin.DOUBLES.obtain(z);
                            Tensor deltaTensor = delta.get(index);
                            @Nullable
                            final double[] deltaArray = deltaTensor.getData();
                            Tensor inputTensor = inData.get(index);
                            @Nullable
                            final double[] inputData = inputTensor.getData();
                            for (int i = 0; i < z; i++) {
                                for (int j = 0; j < y * x; j++) {
                                    //array[i] += deltaArray[i + z * j];
                                    array[i] += deltaArray[i * x * y + j] * inputData[i * x * y + j];
                                }
                            }
                            inputTensor.freeRef();
                            deltaTensor.freeRef();
                            assert Arrays.stream(array).allMatch(v -> Double.isFinite(v));
                            deltaBuffer.addInPlace(array);
                            RecycleBin.DOUBLES.recycle(array, array.length);
                        });
                        deltaBuffer.freeRef();
                    }
                    if (input.isAlive()) {
                        Tensor[] tensors = delta.stream().map(t -> {
                            @Nullable
                            Tensor tensor = t.mapCoords((c) -> t.get(c) * weights[c.getCoords()[2]]);
                            t.freeRef();
                            return tensor;
                        }).toArray(i -> new Tensor[i]);
                        @Nonnull
                        TensorArray tensorArray = TensorArray.wrap(tensors);
                        input.accumulate(buffer, tensorArray);
                    }
                }) {

            @Override
            protected void _free() {
                inData.freeRef();
                input.freeRef();
            }

            @Override
            public boolean isAlive() {
                return input.isAlive() || !isFrozen();
            }
        };
    }

    @Nonnull
    @Override
    public JsonObject getJson(Map<CharSequence, byte[]> resources, DataSerializer dataSerializer) {
        @Nonnull
        final JsonObject json = super.getJsonStub();
        json.add("bias", JsonUtil.getJson(getWeights()));
        return json;
    }

    /**
     * Get wieghts double [ ].
     *
     * @return the double [ ]
     */
    @Nullable
    public double[] getWeights() {
        if (!Arrays.stream(weights).allMatch(v -> Double.isFinite(v))) {
            throw new IllegalStateException(Arrays.toString(weights));
        }
        return weights;
    }

    /**
     * Sets weights.
     *
     * @param f the f
     * @return the weights
     */
    @Nonnull
    public ImgBandScaleLayer setWeights(@Nonnull final IntToDoubleFunction f) {
        @Nullable
        final double[] bias = getWeights();
        for (int i = 0; i < bias.length; i++) {
            bias[i] = f.applyAsDouble(i);
        }
        assert Arrays.stream(bias).allMatch(v -> Double.isFinite(v));
        return this;
    }

    /**
     * Set nn key.
     *
     * @param ds the ds
     * @return the nn key
     */
    @Nonnull
    public Layer set(@Nonnull final double[] ds) {
        @Nullable
        final double[] bias = getWeights();
        for (int i = 0; i < ds.length; i++) {
            bias[i] = ds[i];
        }
        assert Arrays.stream(bias).allMatch(v -> Double.isFinite(v));
        return this;
    }

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