Java tutorial
/* * 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.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.UUID; import java.util.function.DoubleSupplier; import java.util.function.IntToDoubleFunction; /** * Adds a per-color-band value offset to the single tensor input. */ @SuppressWarnings("serial") public class ImgBandBiasLayer extends LayerBase { @SuppressWarnings("unused") private static final Logger log = LoggerFactory.getLogger(ImgBandBiasLayer.class); @Nullable private final double[] bias; /** * Instantiates a new Img band bias key. */ protected ImgBandBiasLayer() { super(); bias = null; } /** * Instantiates a new Img band bias key. * * @param bands the bands */ public ImgBandBiasLayer(final int bands) { super(); bias = new double[bands]; } /** * Instantiates a new Img band bias key. * * @param json the json */ protected ImgBandBiasLayer(@Nonnull final JsonObject json) { super(json); bias = JsonUtil.getDoubleArray(json.getAsJsonArray("bias")); } /** * From json img band bias key. * * @param json the json * @param rs the rs * @return the img band bias key */ public static ImgBandBiasLayer fromJson(@Nonnull final JsonObject json, Map<CharSequence, byte[]> rs) { return new ImgBandBiasLayer(json); } /** * Add double [ ]. * * @param input the input * @return the double [ ] */ @Nonnull public double[] add(@Nonnull final double[] input) { assert Arrays.stream(input).allMatch(v -> Double.isFinite(v)); assert null != input; @Nullable final double[] bias = getBias(); assert null != bias; if (input.length % bias.length != 0) throw new IllegalArgumentException(); @Nonnull final double[] array = new double[input.length]; final int size = input.length / bias.length; for (int i = 0; i < array.length; i++) { array[i] = input[i] + bias[i / size]; } assert Arrays.stream(array).allMatch(v -> Double.isFinite(v)); return array; } /** * Add weights img band bias key. * * @param f the f * @return the img band bias key */ @Nonnull public ImgBandBiasLayer addWeights(@Nonnull final DoubleSupplier f) { Util.add(f, getBias()); 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[] bias = getBias(); input.addRef(); return new Result(TensorArray.wrap(input.getData().stream().parallel().map(r -> { if (r.getDimensions().length != 3) { throw new IllegalArgumentException(Arrays.toString(r.getDimensions())); } if (r.getDimensions()[2] != bias.length) { throw new IllegalArgumentException(String.format("%s: %s does not have %s bands", getName(), Arrays.toString(r.getDimensions()), bias.length)); } @Nonnull Tensor tensor = new Tensor(add(r.getData()), r.getDimensions()); r.freeRef(); return tensor; }).toArray(i -> new Tensor[i])), (@Nonnull final DeltaSet<UUID> buffer, @Nonnull final TensorList data) -> { if (!isFrozen()) { final Delta<UUID> deltaBuffer = buffer.get(ImgBandBiasLayer.this.getId(), bias); data.stream().parallel().forEach(d -> { final double[] array = RecycleBin.DOUBLES.obtain(bias.length); @Nullable final double[] signal = d.getData(); final int size = signal.length / bias.length; for (int i = 0; i < signal.length; i++) { array[i / size] += signal[i]; if (!Double.isFinite(array[i / size])) { array[i / size] = 0.0; } } d.freeRef(); assert Arrays.stream(array).allMatch(v -> Double.isFinite(v)); deltaBuffer.addInPlace(array); RecycleBin.DOUBLES.recycle(array, array.length); }); deltaBuffer.freeRef(); } if (input.isAlive()) { data.addRef(); input.accumulate(buffer, data); } }) { @Override protected void _free() { input.freeRef(); } @Override public boolean isAlive() { return input.isAlive() || !isFrozen(); } }; } /** * Get bias double [ ]. * * @return the double [ ] */ @Nullable public double[] getBias() { if (!Arrays.stream(bias).allMatch(v -> Double.isFinite(v))) { throw new IllegalStateException(Arrays.toString(bias)); } return bias; } @Nonnull @Override public JsonObject getJson(Map<CharSequence, byte[]> resources, DataSerializer dataSerializer) { @Nonnull final JsonObject json = super.getJsonStub(); json.add("bias", JsonUtil.getJson(getBias())); return json; } /** * Set nn key. * * @param ds the ds * @return the nn key */ @Nonnull public Layer set(@Nonnull final double[] ds) { @Nullable final double[] bias = getBias(); for (int i = 0; i < ds.length; i++) { bias[i] = ds[i]; } assert Arrays.stream(bias).allMatch(v -> Double.isFinite(v)); return this; } /** * Sets weights. * * @param f the f * @return the weights */ @Nonnull public ImgBandBiasLayer setWeights(@Nonnull final IntToDoubleFunction f) { @Nullable final double[] bias = getBias(); for (int i = 0; i < bias.length; i++) { bias[i] = f.applyAsDouble(i); } assert Arrays.stream(bias).allMatch(v -> Double.isFinite(v)); return this; } @Nonnull @Override public List<double[]> state() { return Arrays.asList(getBias()); } /** * Sets weights log. * * @param value the value * @return the weights log */ @Nonnull public ImgBandBiasLayer setWeightsLog(final double value) { for (int i = 0; i < bias.length; i++) { bias[i] = (FastRandom.INSTANCE.random() - 0.5) * Math.pow(10, value); } return this; } /** * Sets and free. * * @param tensor the tensor * @return the and free */ public ImgBandBiasLayer setAndFree(final Tensor tensor) { set(tensor.getData()); tensor.freeRef(); return this; } /** * Set img band bias key. * * @param tensor the tensor * @return the img band bias key */ public ImgBandBiasLayer set(final Tensor tensor) { return (ImgBandBiasLayer) set(tensor.getData()); } }