Examples with IntDoubleVector com.tencent.angel.ml.math2.vector.IntDoubleVector used on opensource projects

Example 26 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class MixedBinaryOutZAExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntFloatVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        int base = 0;
        float[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < parts.length; i++) {
            IntDoubleVector part = parts[i];
            IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[i];
            if (part.isDense()) {
                double[] resPartValues = resPart.getValues();
                double[] partValues = part.getStorage().getValues();
                for (int j = 0; j < resPartValues.length; j++) {
                    resPartValues[j] = op.apply(partValues[j], v2Values[base + j]);
                }
            } else if (part.isSparse()) {
                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 {
                // sorted
                if (op.isKeepStorage()) {
                    int[] resPartIndices = resPart.getIndices();
                    double[] resPartValues = resPart.getValues();
                    int[] partIndices = part.getStorage().getIndices();
                    double[] partValues = part.getStorage().getValues();
                    for (int j = 0; j < partIndices.length; j++) {
                        int idx = partIndices[j];
                        resPartIndices[j] = idx;
                        resPartValues[j] = op.apply(partValues[j], v2Values[idx + base]);
                    }
                } else {
                    int[] partIndices = part.getStorage().getIndices();
                    double[] partValues = part.getStorage().getValues();
                    for (int j = 0; j < partIndices.length; j++) {
                        int idx = partIndices[j];
                        resPart.set(idx, op.apply(partValues[j], v2Values[idx + base]));
                    }
                }
            }
            base += part.getDim();
        }
    } else if (v2.isSparse()) {
        ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
        if (v1.size() > v2.size()) {
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            while (iter.hasNext()) {
                Int2FloatMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                int pidx = (int) (idx / subDim);
                int subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getFloatValue()));
                }
            }
        } else {
            int base = 0;
            for (int i = 0; i < parts.length; i++) {
                IntDoubleVector part = parts[i];
                IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[i];
                if (part.isDense()) {
                    double[] partValues = part.getStorage().getValues();
                    double[] resPartValues = resPart.getValues();
                    for (int j = 0; j < partValues.length; j++) {
                        if (v2.hasKey(j + base)) {
                            resPartValues[j] = op.apply(partValues[j], v2.get(j + base));
                        }
                    }
                } else if (part.isSparse()) {
                    ObjectIterator<Int2DoubleMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Int2DoubleMap.Entry entry = piter.next();
                        int idx = entry.getIntKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getDoubleValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        int[] resPartIndices = resPart.getIndices();
                        double[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                            }
                        }
                    }
                }
                base += part.getDim();
            }
        }
    } else {
        // sorted
        if (v1.size() > v2.size()) {
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            int[] v2Indices = v2.getStorage().getIndices();
            float[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2Indices.length; i++) {
                int idx = v2Indices[i];
                int pidx = (int) (idx / subDim);
                int subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
                }
            }
        } else {
            int base = 0;
            for (int i = 0; i < parts.length; i++) {
                IntDoubleVector part = parts[i];
                IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[i];
                if (part.isDense()) {
                    double[] partValues = part.getStorage().getValues();
                    double[] resPartValues = resPart.getValues();
                    for (int j = 0; j < partValues.length; j++) {
                        if (v2.hasKey(j + base)) {
                            resPartValues[j] = op.apply(partValues[j], v2.get(j + base));
                        }
                    }
                } else if (part.isSparse()) {
                    ObjectIterator<Int2DoubleMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Int2DoubleMap.Entry entry = piter.next();
                        int idx = entry.getIntKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getDoubleValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        int[] resPartIndices = resPart.getIndices();
                        double[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                            }
                        }
                    }
                }
                base += part.getDim();
            }
        }
    }
    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++;
    }
    return new CompIntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 27 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class MixedBinaryOutZAExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntIntVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        int base = 0;
        int[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < parts.length; i++) {
            IntDoubleVector part = parts[i];
            IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[i];
            if (part.isDense()) {
                double[] resPartValues = resPart.getValues();
                double[] partValues = part.getStorage().getValues();
                for (int j = 0; j < resPartValues.length; j++) {
                    resPartValues[j] = op.apply(partValues[j], v2Values[base + j]);
                }
            } else if (part.isSparse()) {
                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 {
                // sorted
                if (op.isKeepStorage()) {
                    int[] resPartIndices = resPart.getIndices();
                    double[] resPartValues = resPart.getValues();
                    int[] partIndices = part.getStorage().getIndices();
                    double[] partValues = part.getStorage().getValues();
                    for (int j = 0; j < partIndices.length; j++) {
                        int idx = partIndices[j];
                        resPartIndices[j] = idx;
                        resPartValues[j] = op.apply(partValues[j], v2Values[idx + base]);
                    }
                } else {
                    int[] partIndices = part.getStorage().getIndices();
                    double[] partValues = part.getStorage().getValues();
                    for (int j = 0; j < partIndices.length; j++) {
                        int idx = partIndices[j];
                        resPart.set(idx, op.apply(partValues[j], v2Values[idx + base]));
                    }
                }
            }
            base += part.getDim();
        }
    } else if (v2.isSparse()) {
        ObjectIterator<Int2IntMap.Entry> iter = v2.getStorage().entryIterator();
        if (v1.size() > v2.size()) {
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            while (iter.hasNext()) {
                Int2IntMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                int pidx = (int) (idx / subDim);
                int subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getIntValue()));
                }
            }
        } else {
            int base = 0;
            for (int i = 0; i < parts.length; i++) {
                IntDoubleVector part = parts[i];
                IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[i];
                if (part.isDense()) {
                    double[] partValues = part.getStorage().getValues();
                    double[] resPartValues = resPart.getValues();
                    for (int j = 0; j < partValues.length; j++) {
                        if (v2.hasKey(j + base)) {
                            resPartValues[j] = op.apply(partValues[j], v2.get(j + base));
                        }
                    }
                } else if (part.isSparse()) {
                    ObjectIterator<Int2DoubleMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Int2DoubleMap.Entry entry = piter.next();
                        int idx = entry.getIntKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getDoubleValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        int[] resPartIndices = resPart.getIndices();
                        double[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                            }
                        }
                    }
                }
                base += part.getDim();
            }
        }
    } else {
        // sorted
        if (v1.size() > v2.size()) {
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            int[] v2Indices = v2.getStorage().getIndices();
            int[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2Indices.length; i++) {
                int idx = v2Indices[i];
                int pidx = (int) (idx / subDim);
                int subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
                }
            }
        } else {
            int base = 0;
            for (int i = 0; i < parts.length; i++) {
                IntDoubleVector part = parts[i];
                IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[i];
                if (part.isDense()) {
                    double[] partValues = part.getStorage().getValues();
                    double[] resPartValues = resPart.getValues();
                    for (int j = 0; j < partValues.length; j++) {
                        if (v2.hasKey(j + base)) {
                            resPartValues[j] = op.apply(partValues[j], v2.get(j + base));
                        }
                    }
                } else if (part.isSparse()) {
                    ObjectIterator<Int2DoubleMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Int2DoubleMap.Entry entry = piter.next();
                        int idx = entry.getIntKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getDoubleValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        int[] resPartIndices = resPart.getIndices();
                        double[] resPartValues = resPart.getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPartIndices[j] = idx;
                                resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                            }
                        }
                    } else {
                        int[] partIndices = part.getStorage().getIndices();
                        double[] partValues = part.getStorage().getValues();
                        for (int j = 0; j < partIndices.length; j++) {
                            int idx = partIndices[j];
                            if (v2.hasKey(idx + base)) {
                                resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                            }
                        }
                    }
                }
                base += part.getDim();
            }
        }
    }
    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++;
    }
    return new CompIntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 28 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class MixedBinaryOutNonZAExecutor 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();
    int[] v2Indices = v2.getIndices();
    for (int i = 0; i < v2Indices.length; i++) {
        int gidx = v2Indices[i];
        int pidx = (int) (gidx / subDim);
        int subidx = gidx % subDim;
        ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 1));
    }
    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++;
    }
    return new CompIntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 29 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class MixedBinaryOutNonZAExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntFloatVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        float[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntDoubleVector part : parts) {
            IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[k];
            double[] newValues = resPart.getValues();
            if (part.isDense()) {
                double[] partValue = part.getStorage().getValues();
                for (int i = 0; i < partValue.length; i++) {
                    int idx = i + base;
                    newValues[i] = op.apply(partValue[i], v2Values[idx]);
                }
            } else if (part.isSparse()) {
                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 < newValues.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
                if (op.isKeepStorage()) {
                    int dim = part.getDim();
                    int[] resIndices = resPart.getIndices();
                    double[] resValues = resPart.getValues();
                    int[] partIndices = part.getStorage().getIndices();
                    double[] partValues = part.getStorage().getValues();
                    for (int i = 0; i < dim; i++) {
                        resIndices[i] = i;
                        resValues[i] = op.apply(0, v2Values[i + base]);
                    }
                    int size = part.size();
                    for (int i = 0; i < size; i++) {
                        int idx = partIndices[i];
                        resValues[idx] = op.apply(partValues[i], v2Values[idx + 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++) {
                            newValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            newValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < newValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                newValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                newValues[i] = op.apply(0, v2Values[i + base]);
                            }
                        }
                    }
                }
            }
            base += part.getDim();
            k++;
        }
    } else {
        if (v2.isSparse()) {
            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();
            ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2FloatMap.Entry entry = iter.next();
                int gidx = entry.getIntKey();
                int pidx = (int) (gidx / subDim);
                int subidx = gidx % subDim;
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getFloatValue()));
            }
        } else {
            // sorted
            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();
            int[] v2Indices = v2.getStorage().getIndices();
            float[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2Indices.length; i++) {
                int gidx = v2Indices[i];
                int pidx = (int) (gidx / subDim);
                int subidx = gidx % subDim;
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[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++;
    }
    return new CompIntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 30 with IntDoubleVector

use of com.tencent.angel.ml.math2.vector.IntDoubleVector in project angel by Tencent.

the class MixedDotExecutor method apply.

private static double apply(CompIntDoubleVector v1, IntFloatVector v2) {
    double dotValue = 0.0;
    if (v2.isDense()) {
        int base = 0;
        float[] v2Values = v2.getStorage().getValues();
        for (IntDoubleVector part : v1.getPartitions()) {
            if (part.isDense()) {
                double[] partValues = part.getStorage().getValues();
                for (int i = 0; i < partValues.length; i++) {
                    int idx = base + i;
                    dotValue += partValues[i] * v2Values[idx];
                }
            } else if (part.isSparse()) {
                ObjectIterator<Int2DoubleMap.Entry> iter = part.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = base + entry.getIntKey();
                    dotValue += entry.getDoubleValue() * v2Values[idx];
                }
            } else {
                // isSorted
                int[] partIndices = part.getStorage().getIndices();
                double[] partValues = part.getStorage().getValues();
                for (int i = 0; i < partIndices.length; i++) {
                    int idx = base + partIndices[i];
                    dotValue += partValues[i] * v2Values[idx];
                }
            }
            base += part.getDim();
        }
    } else if (v2.isSparse()) {
        ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Int2FloatMap.Entry entry = iter.next();
            int idx = entry.getIntKey();
            dotValue += v1.get(idx) * entry.getFloatValue();
        }
    } else if (v2.isSorted() && v1.size() > v2.size()) {
        // v2 is sorted
        int[] v2Indices = v2.getStorage().getIndices();
        float[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < v2Indices.length; i++) {
            int idx = v2Indices[i];
            dotValue += v1.get(idx) * v2Values[i];
        }
    } else {
        int base = 0;
        for (IntDoubleVector part : v1.getPartitions()) {
            if (part.isDense()) {
                double[] partValues = part.getStorage().getValues();
                for (int i = 0; i < partValues.length; i++) {
                    int idx = base + i;
                    dotValue += partValues[i] * v2.get(idx);
                }
            } else if (part.isSparse()) {
                ObjectIterator<Int2DoubleMap.Entry> iter = part.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = base + entry.getIntKey();
                    dotValue += entry.getDoubleValue() * v2.get(idx);
                }
            } else {
                // isSorted
                int[] partIndices = part.getStorage().getIndices();
                double[] partValues = part.getStorage().getValues();
                for (int i = 0; i < partIndices.length; i++) {
                    int idx = base + partIndices[i];
                    dotValue += partValues[i] * v2.get(idx);
                }
            }
            base += part.getDim();
        }
    }
    return dotValue;
}