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

Example 31 with LongDoubleVectorStorage

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

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongDoubleVector 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 32 with LongDoubleVectorStorage

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

the class MixedBinaryOutNonZAExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongFloatVector v2, Binary op) {
    LongDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isSparse()) {
        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();
        ObjectIterator<Long2FloatMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Long2FloatMap.Entry entry = iter.next();
            long gidx = entry.getLongKey();
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) 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 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();
        long[] v2Indices = v2.getStorage().getIndices();
        float[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < v2Indices.length; i++) {
            long gidx = v2Indices[i];
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[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 33 with LongDoubleVectorStorage

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

the class MixedBinaryInNonZAExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongFloatVector v2, Binary op) {
    LongDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isSparse()) {
        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();
        ObjectIterator<Long2FloatMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Long2FloatMap.Entry entry = iter.next();
            long gidx = entry.getLongKey();
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) 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 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();
        long[] v2Indices = v2.getStorage().getIndices();
        float[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < v2Indices.length; i++) {
            long gidx = v2Indices[i];
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[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 34 with LongDoubleVectorStorage

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

the class MixedBinaryInNonZAExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongLongVector v2, Binary op) {
    LongDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isSparse()) {
        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();
        ObjectIterator<Long2LongMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Long2LongMap.Entry entry = iter.next();
            long gidx = entry.getLongKey();
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) 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 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();
        long[] v2Indices = v2.getStorage().getIndices();
        long[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < v2Indices.length; i++) {
            long gidx = v2Indices[i];
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[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 35 with LongDoubleVectorStorage

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

the class MixedBinaryInNonZAExecutor method apply.

private static Vector apply(CompLongDoubleVector v1, LongIntVector v2, Binary op) {
    LongDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isSparse()) {
        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();
        ObjectIterator<Long2IntMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Long2IntMap.Entry entry = iter.next();
            long gidx = entry.getLongKey();
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), entry.getIntValue()));
        }
    } else {
        // sorted
        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();
        long[] v2Indices = v2.getStorage().getIndices();
        int[] v2Values = v2.getStorage().getValues();
        for (int i = 0; i < v2Indices.length; i++) {
            long gidx = v2Indices[i];
            int pidx = (int) (gidx / subDim);
            long subidx = gidx % subDim;
            ((LongDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[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;
}