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

Example 21 with IntLongVector

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

the class MixedBinaryOutAllExecutor 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;
                    resPartValues[i] = op.apply(partValue[i], v2Values[idx + base]);
                }
            } 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 < resPart.size(); 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[] resPartIndices = resPart.getIndices();
                    double[] resPartValues = resPart.getValues();
                    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 {
                    double[] resPartValues = resPart.getValues();
                    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++;
    }
    return new CompIntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 22 with IntLongVector

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

the class MixedBinaryOutZAExecutor method apply.

private static Vector apply(CompIntFloatVector v1, IntLongVector v2, Binary op) {
    IntFloatVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        int base = 0;
        long[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < parts.length; i++) {
            IntFloatVector part = parts[i];
            IntFloatVectorStorage resPart = (IntFloatVectorStorage) resParts[i];
            if (part.isDense()) {
                float[] resPartValues = resPart.getValues();
                float[] 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<Int2FloatMap.Entry> iter = part.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    resPart.set(idx, op.apply(entry.getFloatValue(), v2Values[idx + base]));
                }
            } else {
                // sorted
                if (op.isKeepStorage()) {
                    int[] resPartIndices = resPart.getIndices();
                    float[] resPartValues = resPart.getValues();
                    int[] partIndices = part.getStorage().getIndices();
                    float[] 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();
                    float[] 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<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
        if (v1.size() > v2.size()) {
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                int pidx = (int) (idx / subDim);
                int subidx = idx % subDim;
                if (parts[pidx].hasKey(subidx)) {
                    ((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getLongValue()));
                }
            }
        } else {
            int base = 0;
            for (int i = 0; i < parts.length; i++) {
                IntFloatVector part = parts[i];
                IntFloatVectorStorage resPart = (IntFloatVectorStorage) resParts[i];
                if (part.isDense()) {
                    float[] partValues = part.getStorage().getValues();
                    float[] 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<Int2FloatMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Int2FloatMap.Entry entry = piter.next();
                        int idx = entry.getIntKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getFloatValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        int[] partIndices = part.getStorage().getIndices();
                        float[] partValues = part.getStorage().getValues();
                        int[] resPartIndices = resPart.getIndices();
                        float[] 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();
                        float[] 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();
            long[] 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)) {
                    ((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
                }
            }
        } else {
            int base = 0;
            for (int i = 0; i < parts.length; i++) {
                IntFloatVector part = parts[i];
                IntFloatVectorStorage resPart = (IntFloatVectorStorage) resParts[i];
                if (part.isDense()) {
                    float[] partValues = part.getStorage().getValues();
                    float[] 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<Int2FloatMap.Entry> piter = part.getStorage().entryIterator();
                    while (piter.hasNext()) {
                        Int2FloatMap.Entry entry = piter.next();
                        int idx = entry.getIntKey();
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(entry.getFloatValue(), v2.get(idx + base)));
                        }
                    }
                } else {
                    // sorted
                    if (op.isKeepStorage()) {
                        int[] partIndices = part.getStorage().getIndices();
                        float[] partValues = part.getStorage().getValues();
                        int[] resPartIndices = resPart.getIndices();
                        float[] 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();
                        float[] 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();
            }
        }
    }
    IntFloatVector[] res = new IntFloatVector[parts.length];
    int i = 0;
    for (IntFloatVector part : parts) {
        res[i] = new IntFloatVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntFloatVectorStorage) resParts[i]);
        i++;
    }
    return new CompIntFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 23 with IntLongVector

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

the class MixedBinaryOutZAExecutor 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()) {
        int base = 0;
        long[] 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<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
        if (v1.size() > v2.size()) {
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            while (iter.hasNext()) {
                Int2LongMap.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.getLongValue()));
                }
            }
        } 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();
            long[] 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 24 with IntLongVector

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

the class MixedDotExecutor method apply.

private static double apply(CompIntLongVector v1, IntIntVector v2) {
    double dotValue = 0.0;
    if (v2.isDense()) {
        int base = 0;
        int[] v2Values = v2.getStorage().getValues();
        for (IntLongVector part : v1.getPartitions()) {
            if (part.isDense()) {
                long[] 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<Int2LongMap.Entry> iter = part.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int idx = base + entry.getIntKey();
                    dotValue += entry.getLongValue() * v2Values[idx];
                }
            } else {
                // isSorted
                int[] partIndices = part.getStorage().getIndices();
                long[] 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<Int2IntMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Int2IntMap.Entry entry = iter.next();
            int idx = entry.getIntKey();
            dotValue += v1.get(idx) * entry.getIntValue();
        }
    } else if (v2.isSorted() && v1.size() > v2.size()) {
        // v2 is sorted
        int[] v2Indices = v2.getStorage().getIndices();
        int[] 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 (IntLongVector part : v1.getPartitions()) {
            if (part.isDense()) {
                long[] 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<Int2LongMap.Entry> iter = part.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int idx = base + entry.getIntKey();
                    dotValue += entry.getLongValue() * v2.get(idx);
                }
            } else {
                // isSorted
                int[] partIndices = part.getStorage().getIndices();
                long[] 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;
}

Example 25 with IntLongVector

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

the class MixedDotExecutor method apply.

private static double apply(CompIntDoubleVector v1, IntLongVector v2) {
    double dotValue = 0.0;
    if (v2.isDense()) {
        int base = 0;
        long[] 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<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Int2LongMap.Entry entry = iter.next();
            int idx = entry.getIntKey();
            dotValue += v1.get(idx) * entry.getLongValue();
        }
    } else if (v2.isSorted() && v1.size() > v2.size()) {
        // v2 is sorted
        int[] v2Indices = v2.getStorage().getIndices();
        long[] 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;
}