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.JsonArray; import com.google.gson.JsonObject; import com.google.gson.JsonPrimitive; import com.simiacryptus.mindseye.lang.*; import javax.annotation.Nonnull; import javax.annotation.Nullable; import java.util.*; import java.util.stream.IntStream; /** * Selects specific color bands from the input, producing an png apply the same resolution but fewer bands. */ @SuppressWarnings("serial") public class ImgBandSelectLayer extends LayerBase { private final int[] bands; /** * Instantiates a new Img band select key. * * @param bands the bands */ public ImgBandSelectLayer(final int... bands) { super(); this.bands = bands; } /** * Instantiates a new Img band select key. * * @param json the json */ protected ImgBandSelectLayer(@Nonnull final JsonObject json) { super(json); final JsonArray jsonArray = json.getAsJsonArray("bands"); bands = new int[jsonArray.size()]; for (int i = 0; i < bands.length; i++) { bands[i] = jsonArray.get(i).getAsInt(); } } /** * From json img band select key. * * @param json the json * @param rs the rs * @return the img band select key */ public static ImgBandSelectLayer fromJson(@Nonnull final JsonObject json, Map<CharSequence, byte[]> rs) { return new ImgBandSelectLayer(json); } @Nonnull @Override public Result eval(@Nonnull final Result... inObj) { final Result input = inObj[0]; final TensorList batch = input.getData(); @Nonnull final int[] inputDims = batch.getDimensions(); assert 3 == inputDims.length; @Nonnull final Tensor outputDims = new Tensor(inputDims[0], inputDims[1], bands.length); Arrays.stream(inObj).forEach(nnResult -> nnResult.addRef()); @Nonnull TensorArray wrap = TensorArray.wrap( IntStream.range(0, batch.length()).parallel().mapToObj(dataIndex -> outputDims.mapCoords((c) -> { int[] coords = c.getCoords(); @Nullable Tensor tensor = batch.get(dataIndex); double v = tensor.get(coords[0], coords[1], bands[coords[2]]); tensor.freeRef(); return v; })).toArray(i -> new Tensor[i])); outputDims.freeRef(); return new Result(wrap, (@Nonnull final DeltaSet<UUID> buffer, @Nonnull final TensorList error) -> { if (input.isAlive()) { @Nonnull TensorArray tensorArray = TensorArray .wrap(IntStream.range(0, error.length()).parallel().mapToObj(dataIndex -> { @Nonnull final Tensor passback = new Tensor(inputDims); @Nullable final Tensor err = error.get(dataIndex); err.coordStream(false).forEach(c -> { int[] coords = c.getCoords(); passback.set(coords[0], coords[1], bands[coords[2]], err.get(c)); }); err.freeRef(); return passback; }).toArray(i -> new Tensor[i])); input.accumulate(buffer, tensorArray); } }) { @Override protected void _free() { Arrays.stream(inObj).forEach(nnResult -> nnResult.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(); @Nonnull final JsonArray array = new JsonArray(); for (final int b : bands) { array.add(new JsonPrimitive(b)); } json.add("bands", array); return json; } @Nonnull @Override public List<double[]> state() { return new ArrayList<>(); } }