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

Example 11 with LongDoubleSparseVectorStorage

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

the class MixedBinaryOutAllExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongDummyVector v2, Binary op) {
    LongDoubleVector[] 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 LongDoubleSortedVectorStorage) {
                resParts[i] = new LongDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
            }
        }
    }
    long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
    for (int i = 0; i < v1.getDim(); i++) {
        int pidx = (int) (i / subDim);
        long subidx = i % subDim;
        ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
    }
    LongDoubleVector[] res = new LongDoubleVector[parts.length];
    int i = 0;
    for (LongDoubleVector part : parts) {
        res[i] = new LongDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongDoubleVectorStorage) resParts[i]);
        i++;
    }
    return new CompLongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 12 with LongDoubleSparseVectorStorage

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

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongDummyVector v2, Binary op) {
    LongDoubleVector[] 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 LongDoubleSortedVectorStorage) {
                resParts[i] = new LongDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
            }
        }
    }
    long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
    for (int i = 0; i < v1.getDim(); i++) {
        int pidx = (int) (i / subDim);
        long subidx = i % subDim;
        ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
    }
    LongDoubleVector[] res = new LongDoubleVector[parts.length];
    int i = 0;
    for (LongDoubleVector part : parts) {
        res[i] = new LongDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongDoubleVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 13 with LongDoubleSparseVectorStorage

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

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongIntVector v2, Binary op) {
    LongDoubleVector[] 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 LongDoubleSortedVectorStorage) {
                resParts[i] = new LongDoubleSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
            }
        }
    }
    long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
    for (int i = 0; i < v1.getDim(); i++) {
        int pidx = (int) (i / subDim);
        long subidx = i % subDim;
        if (v2.getStorage().hasKey(i)) {
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
        } else {
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
        }
    }
    LongDoubleVector[] res = new LongDoubleVector[parts.length];
    int i = 0;
    for (LongDoubleVector part : parts) {
        res[i] = new LongDoubleVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongDoubleVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 14 with LongDoubleSparseVectorStorage

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

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(LongDoubleVector v1, LongDoubleVector v2, Binary op) {
    LongDoubleVector res;
    if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            // multi-rehash
            LongDoubleVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongDoubleVectorStorage v1Storage = v1.getStorage();
            LongDoubleVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0, 0));
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongDoubleVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongDoubleVectorStorage v1Storage = v1.getStorage();
            LongDoubleVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0, 0));
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongDoubleVectorStorage newStorage = new LongDoubleSparseVectorStorage(v1.getDim());
            LongDoubleVectorStorage v1Storage = v1.getStorage();
            LongDoubleVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else if (v1Storage.hasKey(i) && !v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), 0));
                } else if (!v1Storage.hasKey(i) && v2Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(0, v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0, 0));
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongDoubleVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
            long[] resIndices = newStorage.getIndices();
            double[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            long size1 = v1.size();
            long size2 = v2.size();
            long[] v1Indices = v1.getStorage().getIndices();
            double[] v1Values = v1.getStorage().getValues();
            long[] v2Indices = v2.getStorage().getIndices();
            double[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = Double.NaN;
                }
            }
            int globalPointor = 0;
            while (v1Pointor < size1 && v2Pointor < size2) {
                if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                    resIndices[globalPointor] = v1Indices[v1Pointor];
                    resValues[globalPointor] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                    v1Pointor++;
                    v2Pointor++;
                    globalPointor++;
                } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                    resIndices[globalPointor] = v1Indices[v1Pointor];
                    resValues[globalPointor] = op.apply(v2Values[v2Pointor], 0);
                    v1Pointor++;
                    globalPointor++;
                } else {
                    // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                    resIndices[globalPointor] = v2Indices[v2Pointor];
                    resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
                    v2Pointor++;
                    globalPointor++;
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return res;
}

Example 15 with LongDoubleSparseVectorStorage

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

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(LongDoubleVector v1, LongDummyVector v2, Binary op) {
    LongDoubleVector res;
    if (v1.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            // multi-rehash
            LongDoubleVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongDoubleVectorStorage v1Storage = v1.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0, v2.get(i)));
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        // sorted
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            LongDoubleVectorStorage newStorage = new LongDoubleSparseVectorStorage(v1.getDim());
            LongDoubleVectorStorage v1Storage = v1.getStorage();
            for (int i = 0; i < v1.getDim(); i++) {
                if (v1Storage.hasKey(i)) {
                    newStorage.set(i, op.apply(v1.get(i), v2.get(i)));
                } else {
                    newStorage.set(i, op.apply(0.0, v2.get(i)));
                }
            }
            res = new LongDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    }
    return res;
}