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

Example 61 with IntLongVector

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

the class MixedBinaryOutNonZAExecutor method apply.

private static Vector apply(CompIntLongVector v1, IntLongVector v2, Binary op) {
    IntLongVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        long[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntLongVector part : parts) {
            IntLongVectorStorage resPart = (IntLongVectorStorage) resParts[k];
            long[] newValues = resPart.getValues();
            if (part.isDense()) {
                long[] 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<Int2LongMap.Entry> iter = part.getStorage().entryIterator();
                    while (iter.hasNext()) {
                        Int2LongMap.Entry entry = iter.next();
                        int idx = entry.getIntKey();
                        resPart.set(idx, op.apply(entry.getLongValue(), 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();
                    long[] resValues = resPart.getValues();
                    int[] partIndices = part.getStorage().getIndices();
                    long[] 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();
                        long[] 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 {
                        IntLongVectorStorage 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 IntLongSortedVectorStorage) {
                        resParts[i] = new IntLongSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
                    }
                }
            }
            int subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
            ObjectIterator<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.Entry entry = iter.next();
                int gidx = entry.getIntKey();
                int pidx = (int) (gidx / subDim);
                int subidx = gidx % subDim;
                ((IntLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getLongValue()));
            }
        } else {
            // sorted
            if (!op.isKeepStorage()) {
                for (int i = 0; i < parts.length; i++) {
                    if (parts[i].getStorage() instanceof IntLongSortedVectorStorage) {
                        resParts[i] = new IntLongSparseVectorStorage(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();
            long[] 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;
                ((IntLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
            }
        }
    }
    IntLongVector[] res = new IntLongVector[parts.length];
    int i = 0;
    for (IntLongVector part : parts) {
        res[i] = new IntLongVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (IntLongVectorStorage) resParts[i]);
        i++;
    }
    return new CompIntLongVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 62 with IntLongVector

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

the class MixedBinaryOutNonZAExecutor 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];
            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<Int2LongMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2LongMap.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.getLongValue()));
            }
        } 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();
            long[] 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 63 with IntLongVector

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

the class CompReduceExecutor method apply.

private static UnionEle apply(CompIntLongVector v, ReduceOP op, int start, int end) {
    UnionEle res = new UnionEle();
    IntLongVector[] parts = v.getPartitions();
    switch(op) {
        case Sum:
            for (int i = start; i <= end; i++) {
                res.setDouble1(res.getDouble1() + parts[i].sum());
            }
            break;
        case Avg:
            for (int i = start; i <= end; i++) {
                res.setDouble1(res.getDouble1() + parts[i].sum());
                res.setLong1(res.getLong1() + parts[i].getDim());
            }
            break;
        case Std:
            for (int i = start; i <= end; i++) {
                res.setDouble1(res.getDouble1() + parts[i].sum());
                double norm = parts[i].norm();
                res.setDouble2(res.getDouble2() + norm * norm);
                res.setLong1(res.getLong1() + parts[i].getDim());
            }
            break;
        case Norm:
            for (int i = start; i <= end; i++) {
                double norm = parts[i].norm();
                res.setDouble2(res.getDouble2() + norm * norm);
            }
            break;
        case Min:
            res.setDouble1(Double.MAX_VALUE);
            for (int i = start; i <= end; i++) {
                res.setDouble1(Math.min(res.getDouble1(), parts[i].min()));
            }
            break;
        case Max:
            res.setDouble1(Double.MIN_VALUE);
            for (int i = start; i <= end; i++) {
                res.setDouble1(Math.max(res.getDouble1(), parts[i].max()));
            }
            break;
        case Size:
            for (int i = start; i <= end; i++) {
                res.setLong1(res.getLong1() + parts[i].size());
            }
            break;
        case Numzeros:
            for (int i = start; i <= end; i++) {
                res.setLong1(res.getLong1() + parts[i].numZeros());
            }
            break;
    }
    return res;
}

Example 64 with IntLongVector

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

the class UpdatePSFTest method testDenseLongUDF.

public void testDenseLongUDF() throws Exception {
    Worker worker = LocalClusterContext.get().getWorker(workerAttempt0Id).getWorker();
    MatrixClient client1 = worker.getPSAgent().getMatrixClient(DENSE_LONG_MAT, 0);
    int matrixW1Id = client1.getMatrixId();
    int[] index = genIndexs(feaNum, nnz);
    IntLongVector deltaVec = new IntLongVector(feaNum, new IntLongDenseVectorStorage(feaNum));
    for (int i = 0; i < feaNum; i++) {
        deltaVec.set(i, i);
    }
    deltaVec.setRowId(0);
    Vector[] updates = new Vector[1];
    updates[0] = deltaVec;
    client1.asyncUpdate(new IncrementRows(new IncrementRowsParam(matrixW1Id, updates))).get();
    IntLongVector row = (IntLongVector) client1.getRow(0);
    for (int id : index) {
        // System.out.println("id=" + id + ", value=" + row.get(id));
        Assert.assertEquals(row.get(id), deltaVec.get(id));
    }
    Assert.assertTrue(feaNum == row.size());
}

Example 65 with IntLongVector

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

the class RBIntLongMatrix method diag.

@Override
public Vector diag() {
    long[] resArr = new long[rows.length];
    for (int i = 0; i < rows.length; i++) {
        if (null == rows[i]) {
            resArr[i] = 0;
        } else {
            resArr[i] = rows[i].get(i);
        }
    }
    IntLongDenseVectorStorage storage = new IntLongDenseVectorStorage(resArr);
    return new IntLongVector(getMatrixId(), 0, getClock(), resArr.length, storage);
}