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

Example 76 with IntFloatVector

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

the class DotMatrixExecutor method apply.

private static Vector apply(BlasDoubleMatrix mat, boolean trans, IntFloatVector v) {
    int m = mat.getNumRows(), n = mat.getNumCols();
    double[] resArr;
    if (trans) {
        assert m == v.getDim();
        resArr = new double[n];
    } else {
        assert n == v.getDim();
        resArr = new double[m];
    }
    int r = mat.getNumRows(), c = mat.getNumCols();
    double[] data = mat.getData();
    if (v.isDense()) {
        double[] tempArray = ArrayCopy.copy(v.getStorage().getValues(), new double[v.getDim()]);
        if (trans) {
            blas.dgemv("N", c, r, 1.0, data, c, tempArray, 1, 0.0, resArr, 1);
        } else {
            blas.dgemv("T", c, r, 1.0, data, c, tempArray, 1, 0.0, resArr, 1);
        }
    } else if (v.isSparse()) {
        if (trans) {
            for (int j = 0; j < c; j++) {
                ObjectIterator<Int2FloatMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int i = entry.getIntKey();
                    resArr[j] += data[i * c + j] * entry.getFloatValue();
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                ObjectIterator<Int2FloatMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int j = entry.getIntKey();
                    resArr[i] += data[i * c + j] * entry.getFloatValue();
                }
            }
        }
    } else {
        // sorted
        if (trans) {
            for (int j = 0; j < r; j++) {
                int[] idxs = v.getStorage().getIndices();
                float[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[j] += data[idxs[k] * c + j] * vals[k];
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                int[] idxs = v.getStorage().getIndices();
                float[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[i] += data[i * c + idxs[k]] * vals[k];
                }
            }
        }
    }
    IntDoubleDenseVectorStorage storage = new IntDoubleDenseVectorStorage(resArr);
    return new IntDoubleVector(v.getMatrixId(), v.getClock(), 0, resArr.length, storage);
}

Example 77 with IntFloatVector

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

the class MixedBinaryInAllExecutor 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()) {
        long[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntFloatVector part : parts) {
            IntFloatVectorStorage resPart = (IntFloatVectorStorage) resParts[k];
            if (part.isDense()) {
                float[] partValue = part.getStorage().getValues();
                float[] 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()) {
                float[] 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<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 {
                    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();
                float[] resPartValues = resPart.getValues();
                if (op.isKeepStorage()) {
                    if (part.size() < Constant.denseLoopThreshold * part.getDim()) {
                        int[] partIndices = part.getStorage().getIndices();
                        float[] 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 {
                        IntFloatVectorStorage 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();
                        float[] 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 {
                        IntFloatVectorStorage 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 IntFloatSortedVectorStorage) {
                    resParts[i] = new IntFloatSparseVectorStorage(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)) {
                ((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
            } else {
                ((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
            }
        }
    }
    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++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 78 with IntFloatVector

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

the class MixedBinaryInAllExecutor 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];
            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 79 with IntFloatVector

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

the class RowSplitCombineUtils method combineServerIntFloatRowSplits.

private static Vector combineServerIntFloatRowSplits(List<ServerRow> rowSplits, MatrixMeta matrixMeta, int rowIndex) {
    int colNum = (int) matrixMeta.getColNum();
    int elemNum = 0;
    int size = rowSplits.size();
    for (int i = 0; i < size; i++) {
        elemNum += rowSplits.get(i).size();
    }
    IntFloatVector row;
    if (elemNum >= (int) (storageConvFactor * colNum)) {
        row = VFactory.denseFloatVector(colNum);
    } else {
        row = VFactory.sparseFloatVector(colNum, elemNum);
    }
    row.setMatrixId(matrixMeta.getId());
    row.setRowId(rowIndex);
    Collections.sort(rowSplits, serverRowComp);
    int clock = Integer.MAX_VALUE;
    for (int i = 0; i < size; i++) {
        if (rowSplits.get(i) == null) {
            continue;
        }
        if (rowSplits.get(i).getClock() < clock) {
            clock = rowSplits.get(i).getClock();
        }
        ((ServerIntFloatRow) rowSplits.get(i)).mergeTo(row);
    }
    row.setClock(clock);
    return row;
}

Example 80 with IntFloatVector

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

the class MergeUtils method combineServerIntFloatRowSplits.

private static Vector combineServerIntFloatRowSplits(List<ServerRow> rowSplits, MatrixMeta matrixMeta, int rowIndex) {
    int colNum = (int) matrixMeta.getColNum();
    int elemNum = 0;
    int size = rowSplits.size();
    for (int i = 0; i < size; i++) {
        elemNum += rowSplits.get(i).size();
    }
    IntFloatVector row;
    if (matrixMeta.isHash()) {
        row = VFactory.sparseFloatVector(colNum, elemNum);
    } else {
        if (elemNum >= (int) (storageConvFactor * colNum)) {
            row = VFactory.denseFloatVector(colNum);
        } else {
            row = VFactory.sparseFloatVector(colNum, elemNum);
        }
    }
    row.setMatrixId(matrixMeta.getId());
    row.setRowId(rowIndex);
    Collections.sort(rowSplits, serverRowComp);
    for (int i = 0; i < size; i++) {
        if (rowSplits.get(i) == null) {
            continue;
        }
        ((ServerIntFloatRow) rowSplits.get(i)).mergeTo(row);
    }
    return row;
}