com.simiacryptus.mindseye.layers.java.ImgBandScaleLayer 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.lang.ref.RecycleBin;
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 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 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 buffer, @Nonnull final TensorList delta) -> {
if (!isFrozen()) {
final Delta 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);
}
delta.freeRef();
}) {
@Override
protected void _free() {
inData.freeRef();
input.freeRef();
}
@Override
public boolean isAlive() {
return input.isAlive() || !isFrozen();
}
};
}
@Nonnull
@Override
public JsonObject getJson(Map 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 state() {
return Arrays.asList(getWeights());
}
}