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

Example 41 with LongIntVector

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

the class ByteBufSerdeUtils method serializeLongIntVector.

// LongFloatVector
private static void serializeLongIntVector(ByteBuf out, LongIntVector vector) {
    LongIntVectorStorage storage = vector.getStorage();
    if (storage.isSparse()) {
        serializeInt(out, SPARSE_STORAGE_TYPE);
        serializeInt(out, storage.size());
        ObjectIterator<Long2IntMap.Entry> iter = storage.entryIterator();
        while (iter.hasNext()) {
            Long2IntMap.Entry e = iter.next();
            serializeLong(out, e.getLongKey());
            serializeFloat(out, e.getIntValue());
        }
    } else if (storage.isSorted()) {
        serializeInt(out, SORTED_STORAGE_TYPE);
        long[] indices = vector.getStorage().getIndices();
        int[] values = vector.getStorage().getValues();
        serializeLongs(out, indices);
        serializeInts(out, values);
    } else {
        throw new UnsupportedOperationException("Unsupport storage type " + vector.getStorage().getClass());
    }
}

Example 42 with LongIntVector

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

the class StreamSerdeUtils method deserializeLongIntVector.

private static LongIntVector deserializeLongIntVector(DataInputStream in, long dim) throws IOException {
    int storageType = deserializeInt(in);
    switch(storageType) {
        case SPARSE_STORAGE_TYPE:
            int len = deserializeInt(in);
            Long2IntOpenHashMap idToValueMap = new Long2IntOpenHashMap(len);
            for (int i = 0; i < len; i++) {
                idToValueMap.put(deserializeInt(in), deserializeInt(in));
            }
            return new LongIntVector((int) dim, new LongIntSparseVectorStorage((int) dim, idToValueMap));
        case SORTED_STORAGE_TYPE:
            return VFactory.sortedLongKeyIntVector((int) dim, deserializeLongs(in), deserializeInts(in));
        default:
            throw new UnsupportedOperationException("Unsupport storage type " + storageType);
    }
}

Example 43 with LongIntVector

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

the class MixedBinaryOutZAExecutor method apply.

private static Vector apply(CompLongIntVector v1, LongDummyVector v2, Binary op) {
    LongIntVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v1.size() > v2.size()) {
        long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
        long[] v2Indices = v2.getIndices();
        for (int i = 0; i < v2Indices.length; i++) {
            long idx = v2Indices[i];
            int pidx = (int) (idx / subDim);
            long subidx = idx % subDim;
            if (parts[pidx].hasKey(subidx)) {
                ((LongIntVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 1));
            }
        }
    } else {
        long base = 0;
        for (int i = 0; i < parts.length; i++) {
            LongIntVector part = parts[i];
            LongIntVectorStorage resPart = (LongIntVectorStorage) resParts[i];
            if (part.isDense()) {
                int[] partValues = part.getStorage().getValues();
                int[] 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<Long2IntMap.Entry> piter = part.getStorage().entryIterator();
                while (piter.hasNext()) {
                    Long2IntMap.Entry entry = piter.next();
                    long idx = entry.getLongKey();
                    if (v2.hasKey(idx + base)) {
                        resPart.set(idx, op.apply(entry.getIntValue(), v2.get(idx + base)));
                    }
                }
            } else {
                // sorted
                if (op.isKeepStorage()) {
                    long[] partIndices = part.getStorage().getIndices();
                    int[] partValues = part.getStorage().getValues();
                    long[] resPartIndices = resPart.getIndices();
                    int[] resPartValues = resPart.getValues();
                    for (int j = 0; j < partIndices.length; j++) {
                        long idx = partIndices[j];
                        if (v2.hasKey(idx + base)) {
                            resPartIndices[j] = idx;
                            resPartValues[j] = op.apply(partValues[j], v2.get(idx + base));
                        }
                    }
                } else {
                    long[] partIndices = part.getStorage().getIndices();
                    int[] partValues = part.getStorage().getValues();
                    for (int j = 0; j < partIndices.length; j++) {
                        long idx = partIndices[j];
                        if (v2.hasKey(idx + base)) {
                            resPart.set(idx, op.apply(partValues[j], v2.get(idx + base)));
                        }
                    }
                }
            }
            base += part.getDim();
        }
    }
    LongIntVector[] res = new LongIntVector[parts.length];
    int i = 0;
    for (LongIntVector part : parts) {
        res[i] = new LongIntVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongIntVectorStorage) resParts[i]);
        i++;
    }
    return new CompLongIntVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), res, v1.getSubDim());
}

Example 44 with LongIntVector

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

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(LongFloatVector v1, LongIntVector v2, Binary op) {
    LongFloatVector res;
    if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            // multi-rehash
            LongFloatVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongFloatVectorStorage v1Storage = v1.getStorage();
            LongIntVectorStorage 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(0.0f, 0));
                }
            }
            res = new LongFloatVector(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 {
            LongFloatVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongFloatVectorStorage v1Storage = v1.getStorage();
            LongIntVectorStorage 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(0.0f, 0));
                }
            }
            res = new LongFloatVector(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 {
            LongFloatVectorStorage newStorage = new LongFloatSparseVectorStorage(v1.getDim());
            LongFloatVectorStorage v1Storage = v1.getStorage();
            LongIntVectorStorage 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(0.0f, 0));
                }
            }
            res = new LongFloatVector(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 {
            LongFloatVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
            long[] resIndices = newStorage.getIndices();
            float[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            long size1 = v1.size();
            long size2 = v2.size();
            long[] v1Indices = v1.getStorage().getIndices();
            float[] v1Values = v1.getStorage().getValues();
            long[] v2Indices = v2.getStorage().getIndices();
            int[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = Float.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 LongFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return res;
}

Example 45 with LongIntVector

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

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(LongIntVector v1, LongIntVector v2, Binary op) {
    LongIntVector res;
    if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            // multi-rehash
            LongIntVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongIntVectorStorage v1Storage = v1.getStorage();
            LongIntVectorStorage 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));
                }
            }
            res = new LongIntVector(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 {
            LongIntVectorStorage newStorage = v1.getStorage().emptySparse((int) (v1.getDim()));
            LongIntVectorStorage v1Storage = v1.getStorage();
            LongIntVectorStorage 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));
                }
            }
            res = new LongIntVector(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 {
            LongIntVectorStorage newStorage = new LongIntSparseVectorStorage(v1.getDim());
            LongIntVectorStorage v1Storage = v1.getStorage();
            LongIntVectorStorage 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));
                }
            }
            res = new LongIntVector(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 {
            LongIntVectorStorage newStorage = v1.getStorage().emptySorted((int) (v1.getDim()));
            long[] resIndices = newStorage.getIndices();
            int[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            long size1 = v1.size();
            long size2 = v2.size();
            long[] v1Indices = v1.getStorage().getIndices();
            int[] v1Values = v1.getStorage().getValues();
            long[] v2Indices = v2.getStorage().getIndices();
            int[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                if (size1 != v1.getDim() && size2 != v2.getDim()) {
                    for (int i = 0; i < v1.getDim(); i++) {
                        resValues[i] = 0 / 0;
                    }
                }
            }
            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 LongIntVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return res;
}