Examples with IntDoubleSparseVectorStorage com.tencent.angel.ml.math2.storage.IntDoubleSparseVectorStorage used on opensource projects

Example 16 with IntDoubleSparseVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSparseVectorStorage in project angel by Tencent.

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntLongVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        long[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntDoubleVector part : parts) {
            IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[k];
            if (part.isDense()) {
                double[] partValue = part.getStorage().getValues();
                double[] resPartValues = resPart.getValues();
                for (int i = 0; i < partValue.length; i++) {
                    int idx = i + base;
                    resPartValues[i] = op.apply(partValue[i], v2Values[idx]);
                }
            } else if (part.isSparse()) {
                double[] resPartValues = resPart.getValues();
                if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                    for (int i = 0; i < part.getDim(); i++) {
                        resPart.set(i, op.apply(0, v2Values[i + base]));
                    }
                    ObjectIterator<Int2DoubleMap.Entry> iter = part.getStorage().entryIterator();
                    while (iter.hasNext()) {
                        Int2DoubleMap.Entry entry = iter.next();
                        int idx = entry.getIntKey();
                        resPart.set(idx, op.apply(entry.getDoubleValue(), v2Values[idx + base]));
                    }
                } else {
                    for (int i = 0; i < resPartValues.length; i++) {
                        if (part.getStorage().hasKey(i)) {
                            resPart.set(i, op.apply(part.get(i), v2Values[i + base]));
                        } else {
                            resPart.set(i, op.apply(0, v2Values[i + base]));
                        }
                    }
                }
            } else {
                // sorted
                int[] resPartIndices = resPart.getIndices();
                double[] resPartValues = resPart.getValues();
                if (op.isKeepStorage()) {
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int i = 0; i < part.getDim(); i++) {
                            resPartIndices[i] = i;
                            resPartValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            resPartValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < resPartValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                resPartIndices[i] = i;
                                resPartValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                resPartIndices[i] = i;
                                resPartValues[i] = op.apply(0, v2Values[i + base]);
                            }
                        }
                    }
                } else {
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int i = 0; i < part.getDim(); i++) {
                            resPartValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            resPartValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < resPartValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                resPartValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                resPartValues[i] = op.apply(0, v2Values[i + base]);
                            }
                        }
                    }
                }
            }
            base += part.getDim();
            k++;
        }
    } else {
        if (!op.isKeepStorage()) {
            for (int i = 0; i < parts.length; i++) {
                if (parts[i].getStorage() instanceof IntDoubleSortedVectorStorage) {
                    resParts[i] = new IntDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                }
            }
        }
        int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
        for (int i = 0; i < v1.getDim(); i++) {
            int pidx = (int) (i / subDim);
            int subidx = i % subDim;
            if (v2.getStorage().hasKey(i)) {
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
            } else {
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
            }
        }
    }
    IntDoubleVector[] res = new IntDoubleVector[parts.length];
    int i = 0;
    for (IntDoubleVector part : parts) {
        res[i] = new IntDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntDoubleVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 17 with IntDoubleSparseVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSparseVectorStorage in project angel by Tencent.

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntDummyVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (!op.isKeepStorage()) {
        for (int i = 0; i < parts.length; i++) {
            if (parts[i].getStorage() instanceof IntDoubleSortedVectorStorage) {
                resParts[i] = new IntDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
            }
        }
    }
    int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
    for (int i = 0; i < v1.getDim(); i++) {
        int pidx = (int) (i / subDim);
        int subidx = i % subDim;
        ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
    }
    IntDoubleVector[] res = new IntDoubleVector[parts.length];
    int i = 0;
    for (IntDoubleVector part : parts) {
        res[i] = new IntDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntDoubleVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 18 with IntDoubleSparseVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSparseVectorStorage in project angel by Tencent.

the class CompIntDoubleRowUpdateSplit method serialize.

@Override
public void serialize(ByteBuf buf) {
    super.serialize(buf);
    IntDoubleVectorStorage storage = split.getStorage();
    if (storage instanceof IntDoubleSparseVectorStorage) {
        buf.writeInt(storage.size());
        ObjectIterator<Int2DoubleMap.Entry> iter = storage.entryIterator();
        Int2DoubleMap.Entry entry;
        while (iter.hasNext()) {
            entry = iter.next();
            buf.writeInt(entry.getIntKey());
            buf.writeDouble(entry.getDoubleValue());
        }
    } else if (storage instanceof IntDoubleSortedVectorStorage) {
        buf.writeInt(storage.size());
        int[] indices = storage.getIndices();
        double[] values = storage.getValues();
        for (int i = 0; i < indices.length; i++) {
            buf.writeInt(indices[i]);
            buf.writeDouble(values[i]);
        }
    } else if (storage instanceof IntDoubleDenseVectorStorage) {
        double[] values = storage.getValues();
        int writeSize = values.length < maxItemNum ? values.length : maxItemNum;
        buf.writeInt(writeSize);
        for (int i = 0; i < writeSize; i++) {
            buf.writeDouble(values[i]);
        }
    } else {
        throw new UnsupportedOperationException("unsupport split for storage " + storage.getClass().getName());
    }
}

Example 19 with IntDoubleSparseVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSparseVectorStorage in project angel by Tencent.

the class RangeRouterUtils method splitIntDoubleVector.

public static KeyValuePart[] splitIntDoubleVector(MatrixMeta matrixMeta, IntDoubleVector vector) {
    IntDoubleVectorStorage storage = vector.getStorage();
    if (storage.isSparse()) {
        // Get keys and values
        IntDoubleSparseVectorStorage sparseStorage = (IntDoubleSparseVectorStorage) storage;
        int[] keys = sparseStorage.getIndices();
        double[] values = sparseStorage.getValues();
        return split(matrixMeta, vector.getRowId(), keys, values, false);
    } else if (storage.isDense()) {
        // Get values
        IntDoubleDenseVectorStorage denseStorage = (IntDoubleDenseVectorStorage) storage;
        double[] values = denseStorage.getValues();
        return split(matrixMeta, vector.getRowId(), values);
    } else {
        // Key and value array pair
        IntDoubleSortedVectorStorage sortStorage = (IntDoubleSortedVectorStorage) storage;
        int[] keys = sortStorage.getIndices();
        double[] values = sortStorage.getValues();
        return split(matrixMeta, vector.getRowId(), keys, values, true);
    }
}

Example 20 with IntDoubleSparseVectorStorage

use of com.tencent.angel.ml.math2.storage.IntDoubleSparseVectorStorage in project angel by Tencent.

the class HashRouterUtils method splitIntDoubleVector.

public static void splitIntDoubleVector(KeyHash hasher, MatrixMeta matrixMeta, IntDoubleVector vector, KeyValuePart[] dataParts) {
    int dataPartNum = dataParts.length;
    int dataPartNumMinus1 = dataPartNum - 1;
    if (isPow2(dataPartNum)) {
        IntDoubleVectorStorage storage = vector.getStorage();
        if (storage.isSparse()) {
            // Use iterator
            IntDoubleSparseVectorStorage sparseStorage = (IntDoubleSparseVectorStorage) storage;
            ObjectIterator<Int2DoubleMap.Entry> iter = sparseStorage.entryIterator();
            while (iter.hasNext()) {
                Int2DoubleMap.Entry keyValue = iter.next();
                int partId = computeHashCode(hasher, keyValue.getIntKey()) & dataPartNumMinus1;
                ((HashIntKeysDoubleValuesPart) dataParts[partId]).add(keyValue.getIntKey(), keyValue.getDoubleValue());
            }
        } else if (storage.isDense()) {
            // Get values
            IntDoubleDenseVectorStorage denseStorage = (IntDoubleDenseVectorStorage) storage;
            double[] values = denseStorage.getValues();
            for (int i = 0; i < values.length; i++) {
                int partId = computeHashCode(hasher, i) & dataPartNumMinus1;
                ((HashIntKeysDoubleValuesPart) dataParts[partId]).add(i, values[i]);
            }
        } else {
            // Key and value array pair
            IntDoubleSortedVectorStorage sortStorage = (IntDoubleSortedVectorStorage) storage;
            int[] keys = sortStorage.getIndices();
            double[] values = sortStorage.getValues();
            for (int i = 0; i < keys.length; i++) {
                int partId = computeHashCode(hasher, keys[i]) & dataPartNumMinus1;
                ((HashIntKeysDoubleValuesPart) dataParts[partId]).add(keys[i], values[i]);
            }
        }
    } else {
        IntDoubleVectorStorage storage = vector.getStorage();
        if (storage.isSparse()) {
            // Use iterator
            IntDoubleSparseVectorStorage sparseStorage = (IntDoubleSparseVectorStorage) storage;
            ObjectIterator<Int2DoubleMap.Entry> iter = sparseStorage.entryIterator();
            while (iter.hasNext()) {
                Int2DoubleMap.Entry keyValue = iter.next();
                int partId = computeHashCode(hasher, keyValue.getIntKey()) % dataPartNum;
                ((HashIntKeysDoubleValuesPart) dataParts[partId]).add(keyValue.getIntKey(), keyValue.getDoubleValue());
            }
        } else if (storage.isDense()) {
            // Get values
            IntDoubleDenseVectorStorage denseStorage = (IntDoubleDenseVectorStorage) storage;
            double[] values = denseStorage.getValues();
            for (int i = 0; i < values.length; i++) {
                int partId = computeHashCode(hasher, i) % dataPartNum;
                ((HashIntKeysDoubleValuesPart) dataParts[partId]).add(i, values[i]);
            }
        } else {
            // Key and value array pair
            IntDoubleSortedVectorStorage sortStorage = (IntDoubleSortedVectorStorage) storage;
            int[] keys = sortStorage.getIndices();
            double[] values = sortStorage.getValues();
            for (int i = 0; i < keys.length; i++) {
                int partId = computeHashCode(hasher, keys[i]) % dataPartNum;
                ((HashIntKeysDoubleValuesPart) dataParts[partId]).add(keys[i], values[i]);
            }
        }
    }
}