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

Example 26 with DeltaSet

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

the class ImgTileAssemblyLayer method eval.

@Nonnull
@Override
public Result eval(@Nonnull final Result... inObj) {
    Arrays.stream(inObj).forEach(nnResult -> nnResult.addRef());
    assert 3 == inObj[0].getData().getDimensions().length;
    int[] outputDims = getOutputDims(inObj);
    return new Result(TensorArray.wrap(IntStream.range(0, inObj[0].getData().length()).parallel().mapToObj(dataIndex -> {
        @Nonnull final Tensor outputData = new Tensor(outputDims);
        int totalWidth = 0;
        int totalHeight = 0;
        int inputIndex = 0;
        for (int row = 0; row < rows; row++) {
            int positionX = 0;
            int rowHeight = 0;
            for (int col = 0; col < columns; col++) {
                TensorList tileTensor = inObj[inputIndex].getData();
                int[] tileDimensions = tileTensor.getDimensions();
                rowHeight = Math.max(rowHeight, tileDimensions[1]);
                Tensor inputData = tileTensor.get(dataIndex);
                ImgTileAssemblyLayer.copy(inputData, outputData, positionX, totalHeight);
                inputData.freeRef();
                positionX += tileDimensions[0];
                inputIndex += 1;
            }
            totalHeight += rowHeight;
            totalWidth = Math.max(totalWidth, positionX);
        }
        return outputData;
    }).toArray(i -> new Tensor[i])), (@Nonnull final DeltaSet<Layer> buffer, @Nonnull final TensorList delta) -> {
        int totalHeight = 0;
        int inputIndex = 0;
        for (int row = 0; row < rows; row++) {
            int positionX = 0;
            int rowHeight = 0;
            for (int col = 0; col < columns; col++) {
                Result in = inObj[inputIndex];
                int[] inputDataDimensions = in.getData().getDimensions();
                rowHeight = Math.max(rowHeight, inputDataDimensions[1]);
                if (in.isAlive()) {
                    int _positionX = positionX;
                    int _totalHeight = totalHeight;
                    @Nonnull TensorArray tensorArray = TensorArray.wrap(IntStream.range(0, delta.length()).parallel().mapToObj(dataIndex -> {
                        @Nullable final Tensor deltaTensor = delta.get(dataIndex);
                        @Nonnull final Tensor passbackTensor = new Tensor(inputDataDimensions);
                        ImgTileAssemblyLayer.copy(deltaTensor, passbackTensor, -_positionX, -_totalHeight);
                        deltaTensor.freeRef();
                        return passbackTensor;
                    }).toArray(i -> new Tensor[i]));
                    in.accumulate(buffer, tensorArray);
                }
                positionX += inputDataDimensions[0];
                inputIndex += 1;
            }
            totalHeight += rowHeight;
        }
    }) {

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

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

Example 27 with DeltaSet

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

the class L1NormalizationLayer method eval.

@Nonnull
@Override
public Result eval(@Nonnull final Result... input) {
    Arrays.stream(input).forEach(nnResult -> nnResult.addRef());
    final Result in = input[0];
    final TensorList inData = in.getData();
    inData.addRef();
    return new Result(TensorArray.wrap(IntStream.range(0, inData.length()).mapToObj(dataIndex -> {
        @Nullable final Tensor value = inData.get(dataIndex);
        try {
            final double sum = value.sum();
            if (!Double.isFinite(sum) || 0 == sum) {
                value.addRef();
                return value;
            } else {
                return value.scale(1.0 / sum);
            }
        } finally {
            value.freeRef();
        }
    }).toArray(i -> new Tensor[i])), (@Nonnull final DeltaSet<Layer> buffer, @Nonnull final TensorList outDelta) -> {
        if (in.isAlive()) {
            final Tensor[] passbackArray = IntStream.range(0, outDelta.length()).mapToObj(dataIndex -> {
                Tensor inputTensor = inData.get(dataIndex);
                @Nullable final double[] value = inputTensor.getData();
                Tensor outputTensor = outDelta.get(dataIndex);
                @Nullable final double[] delta = outputTensor.getData();
                final double dot = ArrayUtil.dot(value, delta);
                final double sum = Arrays.stream(value).sum();
                @Nonnull final Tensor passback = new Tensor(outputTensor.getDimensions());
                @Nullable final double[] passbackData = passback.getData();
                if (0 != sum || Double.isFinite(sum)) {
                    for (int i = 0; i < value.length; i++) {
                        passbackData[i] = (delta[i] - dot / sum) / sum;
                    }
                }
                outputTensor.freeRef();
                inputTensor.freeRef();
                return passback;
            }).toArray(i -> new Tensor[i]);
            assert Arrays.stream(passbackArray).flatMapToDouble(x -> Arrays.stream(x.getData())).allMatch(v -> Double.isFinite(v));
            @Nonnull TensorArray tensorArray = TensorArray.wrap(passbackArray);
            in.accumulate(buffer, tensorArray);
        }
    }) {

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

        @Override
        public boolean isAlive() {
            return in.isAlive();
        }
    };
}

Example 28 with DeltaSet

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

the class MomentumStrategy method orient.

@Nonnull
@Override
public SimpleLineSearchCursor orient(final Trainable subject, @Nonnull final PointSample measurement, final TrainingMonitor monitor) {
    final LineSearchCursor orient = inner.orient(subject, measurement, monitor);
    final DeltaSet<Layer> direction = ((SimpleLineSearchCursor) orient).direction;
    @Nonnull final DeltaSet<Layer> newDelta = new DeltaSet<Layer>();
    direction.getMap().forEach((layer, delta) -> {
        final DoubleBuffer<Layer> prevBuffer = prevDelta.get(layer, delta.target);
        newDelta.get(layer, delta.target).addInPlace(ArrayUtil.add(ArrayUtil.multiply(prevBuffer.getDelta(), carryOver), delta.getDelta()));
    });
    prevDelta = newDelta;
    return new SimpleLineSearchCursor(subject, measurement, newDelta);
}

Example 29 with DeltaSet

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

the class SingleDerivativeTester method testUnFrozen.

/**
 * Test un frozen.
 *
 * @param component      the component
 * @param inputPrototype the input prototype
 */
public void testUnFrozen(@Nonnull final Layer component, Tensor[] inputPrototype) {
    inputPrototype = Arrays.stream(inputPrototype).map(tensor -> tensor.copy()).toArray(i -> new Tensor[i]);
    @Nonnull final AtomicBoolean reachedInputFeedback = new AtomicBoolean(false);
    @Nonnull final Layer frozen = component.copy().setFrozen(false);
    List<TensorArray> inputCopies = Arrays.stream(inputPrototype).map(TensorArray::wrap).collect(Collectors.toList());
    Result[] inputs = inputCopies.stream().map(tensor -> new Result(tensor, (@Nonnull final DeltaSet<Layer> buffer, @Nonnull final TensorList data) -> {
        reachedInputFeedback.set(true);
    }) {

        @Override
        public boolean isAlive() {
            return true;
        }
    }).toArray(i -> new Result[i]);
    @Nullable final Result eval;
    try {
        eval = frozen.eval(inputs);
    } finally {
        for (@Nonnull Result result : inputs) {
            result.freeRef();
        }
        for (@Nonnull TensorArray tensorArray : inputCopies) {
            tensorArray.freeRef();
        }
    }
    @Nonnull final DeltaSet<Layer> buffer = new DeltaSet<Layer>();
    TensorList tensorList = eval.getData();
    eval.accumulate(buffer, tensorList);
    eval.freeRef();
    @Nullable final List<double[]> stateList = frozen.state();
    final List<Delta<Layer>> deltas = stateList.stream().map(doubles -> {
        return buffer.stream().filter(x -> x.target == doubles).findFirst().orElse(null);
    }).filter(x -> x != null).collect(Collectors.toList());
    if (deltas.isEmpty() && !stateList.isEmpty()) {
        throw new AssertionError("Nonfrozen component not listed in delta. Deltas: " + deltas);
    }
    frozen.freeRef();
    buffer.freeRef();
    if (!reachedInputFeedback.get() && inputPrototype.length != 0) {
        throw new RuntimeException("Nonfrozen component did not pass input backwards");
    }
}

Example 30 with DeltaSet

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

the class ObjectLocation method renderAlpha.

/**
 * Render alpha tensor.
 *
 * @param alphaPower     the alpha power
 * @param img            the img
 * @param locationResult the location result
 * @param classification the classification
 * @param category       the category
 * @return the tensor
 */
public Tensor renderAlpha(final double alphaPower, final Tensor img, final Result locationResult, final Tensor classification, final int category) {
    TensorArray tensorArray = TensorArray.wrap(new Tensor(classification.getDimensions()).set(category, 1));
    DeltaSet<Layer> deltaSet = new DeltaSet<>();
    locationResult.accumulate(deltaSet, tensorArray);
    double[] rawDelta = deltaSet.getMap().entrySet().stream().filter(x -> x.getValue().target == img.getData()).findAny().get().getValue().getDelta();
    Tensor deltaColor = new Tensor(rawDelta, img.getDimensions()).mapAndFree(x -> Math.abs(x));
    Tensor delta1d = blur(reduce(deltaColor), 3);
    return TestUtil.normalizeBands(TestUtil.normalizeBands(delta1d, 1).mapAndFree(x -> Math.pow(x, alphaPower)));
}