com.simiacryptus.mindseye.layers.java.MaxImageBandLayer Maven / Gradle / Ivy
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Pure Java Neural Networks Components
/*
* Copyright (c) 2019 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 org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import javax.annotation.Nonnull;
import javax.annotation.Nullable;
import java.util.*;
import java.util.stream.DoubleStream;
import java.util.stream.IntStream;
/**
* Selects the highest value in each color band, emitting a 1x1xN tensor.
*/
@SuppressWarnings("serial")
public class MaxImageBandLayer extends LayerBase {
@SuppressWarnings("unused")
private static final Logger log = LoggerFactory.getLogger(MaxImageBandLayer.class);
/**
* Instantiates a new Max png band key.
*/
public MaxImageBandLayer() {
super();
}
/**
* Instantiates a new Max png band key.
*
* @param id the id
* @param kernelDims the kernel dims
*/
protected MaxImageBandLayer(@Nonnull final JsonObject id, final int... kernelDims) {
super(id);
}
/**
* From json max png band key.
*
* @param json the json
* @param rs the rs
* @return the max png band key
*/
public static MaxImageBandLayer fromJson(@Nonnull final JsonObject json, Map rs) {
return new MaxImageBandLayer(json,
JsonUtil.getIntArray(json.getAsJsonArray("heapCopy")));
}
@Nonnull
@Override
public Result eval(@Nonnull final Result... inObj) {
assert 1 == inObj.length;
final TensorList inputData = inObj[0].getData();
inputData.addRef();
inputData.length();
@Nonnull final int[] inputDims = inputData.getDimensions();
assert 3 == inputDims.length;
Arrays.stream(inObj).forEach(nnResult -> nnResult.addRef());
final Coordinate[][] maxCoords = inputData.stream().map(data -> {
Coordinate[] coordinates = IntStream.range(0, inputDims[2]).mapToObj(band -> {
return data.coordStream(true).filter(e -> e.getCoords()[2] == band).max(Comparator.comparing(c -> data.get(c))).get();
}).toArray(i -> new Coordinate[i]);
data.freeRef();
return coordinates;
}).toArray(i -> new Coordinate[i][]);
return new Result(TensorArray.wrap(IntStream.range(0, inputData.length()).mapToObj(dataIndex -> {
Tensor tensor = inputData.get(dataIndex);
final DoubleStream doubleStream = IntStream.range(0, inputDims[2]).mapToDouble(band -> {
final int[] maxCoord = maxCoords[dataIndex][band].getCoords();
double v = tensor.get(maxCoord[0], maxCoord[1], band);
return v;
});
Tensor tensor1 = new Tensor(1, 1, inputDims[2]).set(Tensor.getDoubles(doubleStream, inputDims[2]));
tensor.freeRef();
return tensor1;
}).toArray(i -> new Tensor[i])), (@Nonnull final DeltaSet buffer, @Nonnull final TensorList delta) -> {
if (inObj[0].isAlive()) {
@Nonnull TensorArray tensorArray = TensorArray.wrap(IntStream.range(0, delta.length()).parallel().mapToObj(dataIndex -> {
Tensor deltaTensor = delta.get(dataIndex);
@Nonnull final Tensor passback = new Tensor(inputData.getDimensions());
IntStream.range(0, inputDims[2]).forEach(b -> {
final int[] maxCoord = maxCoords[dataIndex][b].getCoords();
passback.set(new int[]{maxCoord[0], maxCoord[1], b}, deltaTensor.get(0, 0, b));
});
deltaTensor.freeRef();
return passback;
}).toArray(i -> new Tensor[i]));
inObj[0].accumulate(buffer, tensorArray);
}
}) {
@Override
protected void _free() {
Arrays.stream(inObj).forEach(nnResult -> nnResult.freeRef());
inputData.freeRef();
}
@Override
public boolean isAlive() {
return inObj[0].isAlive();
}
};
}
@Nonnull
@Override
public JsonObject getJson(Map resources, DataSerializer dataSerializer) {
@Nonnull final JsonObject json = super.getJsonStub();
return json;
}
@Nonnull
@Override
public List state() {
return Arrays.asList();
}
/**
* The type Calc regions parameter.
*/
public static class CalcRegionsParameter {
/**
* The Input dims.
*/
public int[] inputDims;
/**
* The Kernel dims.
*/
public int[] kernelDims;
/**
* Instantiates a new Calc regions parameter.
*
* @param inputDims the input dims
* @param kernelDims the kernel dims
*/
public CalcRegionsParameter(final int[] inputDims, final int[] kernelDims) {
this.inputDims = inputDims;
this.kernelDims = kernelDims;
}
@Override
public boolean equals(@Nullable final Object obj) {
if (this == obj) {
return true;
}
if (obj == null) {
return false;
}
if (getClass() != obj.getClass()) {
return false;
}
@Nonnull final MaxImageBandLayer.CalcRegionsParameter other = (MaxImageBandLayer.CalcRegionsParameter) obj;
if (!Arrays.equals(inputDims, other.inputDims)) {
return false;
}
return Arrays.equals(kernelDims, other.kernelDims);
}
@Override
public int hashCode() {
final int prime = 31;
int result = 1;
result = prime * result + Arrays.hashCode(inputDims);
result = prime * result + Arrays.hashCode(kernelDims);
return result;
}
}
}