Examples with Layer com.simiacryptus.mindseye.lang.Layer used on opensource projects

Example 96 with Layer

use of com.simiacryptus.mindseye.lang.Layer in project MindsEye by SimiaCryptus.

the class AvgPoolingLayer method eval.

@Nonnull
@SuppressWarnings("unchecked")
@Override
public Result eval(@Nonnull final Result... inObj) {
    final int kernelSize = Tensor.length(kernelDims);
    final TensorList data = inObj[0].getData();
    @Nonnull final int[] inputDims = data.getDimensions();
    final int[] newDims = IntStream.range(0, inputDims.length).map(i -> {
        assert 0 == inputDims[i] % kernelDims[i] : inputDims[i] + ":" + kernelDims[i];
        return inputDims[i] / kernelDims[i];
    }).toArray();
    final Map<Coordinate, List<int[]>> coordMap = AvgPoolingLayer.getCoordMap(kernelDims, newDims);
    final Tensor[] outputValues = IntStream.range(0, data.length()).mapToObj(dataIndex -> {
        @Nullable final Tensor input = data.get(dataIndex);
        @Nonnull final Tensor output = new Tensor(newDims);
        for (@Nonnull final Entry<Coordinate, List<int[]>> entry : coordMap.entrySet()) {
            double sum = entry.getValue().stream().mapToDouble(inputCoord -> input.get(inputCoord)).sum();
            if (Double.isFinite(sum)) {
                output.add(entry.getKey(), sum / kernelSize);
            }
        }
        input.freeRef();
        return output;
    }).toArray(i -> new Tensor[i]);
    Arrays.stream(inObj).forEach(nnResult -> nnResult.addRef());
    return new Result(TensorArray.wrap(outputValues), (@Nonnull final DeltaSet<Layer> buffer, @Nonnull final TensorList delta) -> {
        if (inObj[0].isAlive()) {
            final Tensor[] passback = IntStream.range(0, delta.length()).mapToObj(dataIndex -> {
                @Nullable Tensor tensor = delta.get(dataIndex);
                @Nonnull final Tensor backSignal = new Tensor(inputDims);
                for (@Nonnull final Entry<Coordinate, List<int[]>> outputMapping : coordMap.entrySet()) {
                    final double outputValue = tensor.get(outputMapping.getKey());
                    for (@Nonnull final int[] inputCoord : outputMapping.getValue()) {
                        backSignal.add(inputCoord, outputValue / kernelSize);
                    }
                }
                tensor.freeRef();
                return backSignal;
            }).toArray(i -> new Tensor[i]);
            @Nonnull TensorArray tensorArray = TensorArray.wrap(passback);
            inObj[0].accumulate(buffer, tensorArray);
        }
    }) {

        @Override
        protected void _free() {
            Arrays.stream(inObj).forEach(nnResult -> nnResult.freeRef());
        }

        @Override
        public boolean isAlive() {
            return inObj[0].isAlive();
        }
    };
}

Example 97 with Layer

use of com.simiacryptus.mindseye.lang.Layer in project MindsEye by SimiaCryptus.

the class FullyConnectedReferenceLayer method eval.

@Nonnull
@Override
public Result eval(final Result... inObj) {
    final Result inputResult = inObj[0];
    final TensorList indata = inputResult.getData();
    inputResult.addRef();
    indata.addRef();
    @Nonnull int[] inputDimensions = indata.getDimensions();
    assert Tensor.length(inputDimensions) == Tensor.length(this.inputDims) : Arrays.toString(inputDimensions) + " == " + Arrays.toString(this.inputDims);
    weights.addRef();
    return new Result(TensorArray.wrap(IntStream.range(0, indata.length()).mapToObj(index -> {
        @Nullable final Tensor input = indata.get(index);
        @Nullable final Tensor output = new Tensor(outputDims);
        weights.coordStream(false).forEach(c -> {
            int[] coords = c.getCoords();
            double prev = output.get(coords[1]);
            double w = weights.get(c);
            double i = input.get(coords[0]);
            double value = prev + w * i;
            output.set(coords[1], value);
        });
        input.freeRef();
        return output;
    }).toArray(i -> new Tensor[i])), (@Nonnull final DeltaSet<Layer> buffer, @Nonnull final TensorList delta) -> {
        if (!isFrozen()) {
            final Delta<Layer> deltaBuffer = buffer.get(FullyConnectedReferenceLayer.this, getWeights().getData());
            Tensor[] array = IntStream.range(0, indata.length()).mapToObj(i -> {
                @Nullable final Tensor inputTensor = indata.get(i);
                @Nullable final Tensor deltaTensor = delta.get(i);
                @Nonnull Tensor weights = new Tensor(FullyConnectedReferenceLayer.this.weights.getDimensions());
                weights.coordStream(false).forEach(c -> {
                    int[] coords = c.getCoords();
                    weights.set(c, inputTensor.get(coords[0]) * deltaTensor.get(coords[1]));
                });
                inputTensor.freeRef();
                deltaTensor.freeRef();
                return weights;
            }).toArray(i -> new Tensor[i]);
            Tensor tensor = Arrays.stream(array).reduce((a, b) -> {
                Tensor c = a.addAndFree(b);
                b.freeRef();
                return c;
            }).get();
            deltaBuffer.addInPlace(tensor.getData()).freeRef();
            tensor.freeRef();
        }
        if (inputResult.isAlive()) {
            @Nonnull final TensorList tensorList = TensorArray.wrap(IntStream.range(0, indata.length()).mapToObj(i -> {
                @Nullable final Tensor inputTensor = new Tensor(inputDims);
                @Nullable final Tensor deltaTensor = delta.get(i);
                weights.coordStream(false).forEach(c -> {
                    int[] coords = c.getCoords();
                    inputTensor.set(coords[0], inputTensor.get(coords[0]) + weights.get(c) * deltaTensor.get(coords[1]));
                });
                deltaTensor.freeRef();
                return inputTensor;
            }).toArray(i -> new Tensor[i]));
            inputResult.accumulate(buffer, tensorList);
        }
    }) {

        @Override
        protected void _free() {
            indata.freeRef();
            inputResult.freeRef();
            weights.freeRef();
        }

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

Example 98 with Layer

use of com.simiacryptus.mindseye.lang.Layer in project MindsEye by SimiaCryptus.

the class GaussianNoiseLayer method eval.

@Nonnull
@Override
public Result eval(final Result... inObj) {
    final Result in0 = inObj[0];
    final TensorList inputData = in0.getData();
    final int itemCnt = inputData.length();
    in0.addRef();
    inputData.addRef();
    final Tensor[] outputA = IntStream.range(0, itemCnt).mapToObj(dataIndex -> {
        @Nonnull final Random random = new Random(seed);
        @Nullable final Tensor input = inputData.get(dataIndex);
        @Nullable final Tensor output = input.map(x -> {
            return x + random.nextGaussian() * getValue();
        });
        input.freeRef();
        return output;
    }).toArray(i -> new Tensor[i]);
    return new Result(TensorArray.wrap(outputA), (@Nonnull final DeltaSet<Layer> buffer, @Nonnull final TensorList delta) -> {
        if (in0.isAlive()) {
            @Nonnull TensorArray tensorArray = TensorArray.wrap(IntStream.range(0, delta.length()).mapToObj(dataIndex -> {
                Tensor tensor = delta.get(dataIndex);
                @Nullable final double[] deltaData = tensor.getData();
                @Nonnull final Tensor passback = new Tensor(inputData.getDimensions());
                for (int i = 0; i < passback.length(); i++) {
                    passback.set(i, deltaData[i]);
                }
                tensor.freeRef();
                return passback;
            }).toArray(i -> new Tensor[i]));
            in0.accumulate(buffer, tensorArray);
        }
    }) {

        @Override
        protected void _free() {
            inputData.freeRef();
            in0.freeRef();
        }

        @Override
        public boolean isAlive() {
            return in0.isAlive() || !isFrozen();
        }
    };
}

Example 99 with Layer

use of com.simiacryptus.mindseye.lang.Layer in project MindsEye by SimiaCryptus.

the class ImgBandBiasLayer method eval.

/**
 * 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<Layer> buffer, @Nonnull final TensorList data) -> {
        if (!isFrozen()) {
            final Delta<Layer> deltaBuffer = buffer.get(ImgBandBiasLayer.this, 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();
        }
    };
}

Example 100 with Layer

use of com.simiacryptus.mindseye.lang.Layer in project MindsEye by SimiaCryptus.

the class ImgBandSelectLayer method eval.

@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<Layer> 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();
        }
    };
}