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

Example 96 with DeltaSet

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

the class RecursiveSubspace method buildSubspace.

/**
 * Build subspace nn layer.
 *
 * @param subject     the subject
 * @param measurement the measurement
 * @param monitor     the monitor
 * @return the nn layer
 */
@Nullable
public Layer buildSubspace(@Nonnull Trainable subject, @Nonnull PointSample measurement, @Nonnull TrainingMonitor monitor) {
    @Nonnull PointSample origin = measurement.copyFull().backup();
    @Nonnull final DeltaSet<Layer> direction = measurement.delta.scale(-1);
    final double magnitude = direction.getMagnitude();
    if (Math.abs(magnitude) < 1e-10) {
        monitor.log(String.format("Zero gradient: %s", magnitude));
    } else if (Math.abs(magnitude) < 1e-5) {
        monitor.log(String.format("Low gradient: %s", magnitude));
    }
    boolean hasPlaceholders = direction.getMap().entrySet().stream().filter(x -> x.getKey() instanceof PlaceholderLayer).findAny().isPresent();
    List<Layer> deltaLayers = direction.getMap().entrySet().stream().map(x -> x.getKey()).filter(x -> !(x instanceof PlaceholderLayer)).collect(Collectors.toList());
    int size = deltaLayers.size() + (hasPlaceholders ? 1 : 0);
    if (null == weights || weights.length != size)
        weights = new double[size];
    return new LayerBase() {

        @Nonnull
        Layer self = this;

        @Nonnull
        @Override
        public Result eval(Result... array) {
            assertAlive();
            origin.restore();
            IntStream.range(0, deltaLayers.size()).forEach(i -> {
                direction.getMap().get(deltaLayers.get(i)).accumulate(weights[hasPlaceholders ? (i + 1) : i]);
            });
            if (hasPlaceholders) {
                direction.getMap().entrySet().stream().filter(x -> x.getKey() instanceof PlaceholderLayer).distinct().forEach(entry -> entry.getValue().accumulate(weights[0]));
            }
            PointSample measure = subject.measure(monitor);
            double mean = measure.getMean();
            monitor.log(String.format("RecursiveSubspace: %s <- %s", mean, Arrays.toString(weights)));
            direction.addRef();
            return new Result(TensorArray.wrap(new Tensor(mean)), (DeltaSet<Layer> buffer, TensorList data) -> {
                DoubleStream deltaStream = deltaLayers.stream().mapToDouble(layer -> {
                    Delta<Layer> a = direction.getMap().get(layer);
                    Delta<Layer> b = measure.delta.getMap().get(layer);
                    return b.dot(a) / Math.max(Math.sqrt(a.dot(a)), 1e-8);
                });
                if (hasPlaceholders) {
                    deltaStream = DoubleStream.concat(DoubleStream.of(direction.getMap().keySet().stream().filter(x -> x instanceof PlaceholderLayer).distinct().mapToDouble(layer -> {
                        Delta<Layer> a = direction.getMap().get(layer);
                        Delta<Layer> b = measure.delta.getMap().get(layer);
                        return b.dot(a) / Math.max(Math.sqrt(a.dot(a)), 1e-8);
                    }).sum()), deltaStream);
                }
                buffer.get(self, weights).addInPlace(deltaStream.toArray()).freeRef();
            }) {

                @Override
                protected void _free() {
                    measure.freeRef();
                    direction.freeRef();
                }

                @Override
                public boolean isAlive() {
                    return true;
                }
            };
        }

        @Override
        protected void _free() {
            direction.freeRef();
            origin.freeRef();
            super._free();
        }

        @Nonnull
        @Override
        public JsonObject getJson(Map<CharSequence, byte[]> resources, DataSerializer dataSerializer) {
            throw new IllegalStateException();
        }

        @Nullable
        @Override
        public List<double[]> state() {
            return null;
        }
    };
}

Example 97 with DeltaSet

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

the class SimpleEval method call.

@Nonnull
@Override
public SimpleEval call() {
    Tensor[] inputCopy = Arrays.stream(input).map(x -> x.copy()).toArray(i -> new Tensor[i]);
    derivative = Arrays.stream(inputCopy).map(input -> new Tensor(input.getDimensions())).toArray(i -> new Tensor[i]);
    Result[] input = IntStream.range(0, inputCopy.length).mapToObj(i -> {
        return new Result(TensorArray.create(inputCopy[i]), (@Nonnull final DeltaSet<Layer> buffer, @Nonnull final TensorList data) -> {
            data.stream().forEach(t -> {
                derivative[i].addInPlace(t);
                t.freeRef();
            });
        }) {

            @Override
            protected void _free() {
            }

            @Override
            public boolean isAlive() {
                return true;
            }
        };
    }).toArray(i -> new Result[i]);
    @Nullable final Result eval;
    try {
        eval = layer.eval(input);
    } finally {
        for (@Nonnull Result result : input) {
            result.getData().freeRef();
            result.freeRef();
        }
        for (@Nonnull Tensor tensor : inputCopy) {
            tensor.freeRef();
        }
    }
    TensorList evalData = eval.getData();
    TensorList outputTensorList = evalData.copy();
    @Nullable Tensor outputTensor = outputTensorList.get(0);
    @Nonnull DeltaSet<Layer> deltaSet = new DeltaSet<>();
    try {
        synchronized (this) {
            if (null != output) {
                output.freeRef();
                output = null;
            }
        }
        output = outputTensor.copy();
        @Nonnull TensorList tensorList = getFeedback(outputTensorList);
        eval.accumulate(deltaSet, tensorList);
        return this;
    } finally {
        outputTensor.freeRef();
        evalData.freeRef();
        outputTensorList.freeRef();
        eval.freeRef();
        deltaSet.freeRef();
    }
}

Example 98 with DeltaSet

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

the class SimpleListEval method call.

@Nonnull
@Override
public SimpleResult call() {
    TensorList[] inputCopy = Arrays.stream(input).map(x -> x.copy()).toArray(i -> new TensorList[i]);
    inputDerivative = Arrays.stream(inputCopy).map(tensorList -> TensorArray.wrap(tensorList.stream().map(i -> {
        @Nonnull Tensor tensor = new Tensor(i.getDimensions());
        i.freeRef();
        return tensor;
    }).toArray(i -> new Tensor[i]))).toArray(i -> new TensorList[i]);
    Result[] inputs = IntStream.range(0, inputCopy.length).mapToObj(i -> {
        return new Result(inputCopy[i], (@Nonnull final DeltaSet<Layer> buffer, @Nonnull final TensorList data) -> {
            SimpleListEval.accumulate(inputDerivative[i], data);
        }) {

            @Override
            public boolean isAlive() {
                return true;
            }
        };
    }).toArray(i -> new Result[i]);
    @Nullable final Result eval = layer.eval(inputs);
    for (@Nonnull Result result : inputs) {
        result.freeRef();
    }
    TensorList outputData = eval.getData().copy();
    for (@Nonnull TensorList tensorList : inputCopy) {
        tensorList.freeRef();
    }
    eval.getData().freeRef();
    @Nonnull TensorList tensorList = getFeedback(outputData);
    this.layerDerivative.freeRef();
    this.layerDerivative = new DeltaSet<>();
    eval.accumulate(layerDerivative, tensorList);
    eval.freeRef();
    output = outputData;
    return this;
}