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

Example 26 with Storage

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

the class MixedBinaryInNonZAExecutor method apply.

private static Vector apply(CompLongLongVector v1, LongIntVector v2, Binary op) {
    LongLongVector[] 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 LongLongSortedVectorStorage) {
                    resParts[i] = new LongLongSparseVectorStorage(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;
            ((LongLongVectorStorage) 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 LongLongSortedVectorStorage) {
                    resParts[i] = new LongLongSparseVectorStorage(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;
            ((LongLongVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
        }
    }
    LongLongVector[] res = new LongLongVector[parts.length];
    int i = 0;
    for (LongLongVector part : parts) {
        res[i] = new LongLongVector(part.getMatrixId(), part.getRowId(), part.getClock(), part.getDim(), (LongLongVectorStorage) resParts[i]);
        i++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 27 with Storage

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

the class MixedBinaryInNonZAExecutor method apply.

private static Vector apply(CompIntFloatVector v1, IntFloatVector v2, Binary op) {
    IntFloatVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        float[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntFloatVector part : parts) {
            IntFloatVectorStorage resPart = (IntFloatVectorStorage) resParts[k];
            float[] newValues = resPart.getValues();
            if (part.isDense()) {
                float[] 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<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 < 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();
                    float[] resValues = resPart.getValues();
                    int[] partIndices = part.getStorage().getIndices();
                    float[] partValues = part.getStorage().getValues();
                    for (int i = 0; i < dim; i++) {
                        resIndices[i] = i;
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                    int size = v1.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();
                        float[] 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 {
                        IntFloatVectorStorage 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 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();
        ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Int2FloatMap.Entry entry = iter.next();
            int gidx = entry.getIntKey();
            int pidx = (int) (gidx / subDim);
            int subidx = gidx % subDim;
            ((IntFloatVectorStorage) 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 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();
        int[] v2Indices = v2.getStorage().getIndices();
        float[] 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;
            ((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
        }
    }
    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 28 with Storage

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

the class MixedBinaryInNonZAExecutor 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];
            float[] newValues = resPart.getValues();
            if (part.isDense()) {
                float[] 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<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 < 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();
                    float[] resValues = resPart.getValues();
                    int[] partIndices = part.getStorage().getIndices();
                    float[] partValues = part.getStorage().getValues();
                    for (int i = 0; i < dim; i++) {
                        resIndices[i] = i;
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                    int size = v1.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();
                        float[] 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 {
                        IntFloatVectorStorage 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 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();
        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;
            ((IntFloatVectorStorage) 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 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();
        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;
            ((IntFloatVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2Values[i]));
        }
    }
    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 29 with Storage

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

the class MixedBinaryInNonZAExecutor method apply.

private static Vector apply(CompLongIntVector v1, LongDummyVector v2, Binary op) {
    LongIntVector[] 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 LongIntSortedVectorStorage) {
                resParts[i] = new LongIntSparseVectorStorage(parts[i].getDim(), parts[i].getStorage().getIndices(), parts[i].getStorage().getValues());
            }
        }
    }
    long subDim = (v1.getDim() + v1.getNumPartitions() - 1) / v1.getNumPartitions();
    long[] v2Indices = v2.getIndices();
    for (int i = 0; i < v2Indices.length; i++) {
        long gidx = v2Indices[i];
        int pidx = (int) (gidx / subDim);
        long subidx = gidx % subDim;
        ((LongIntVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 1));
    }
    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++;
    }
    v1.setPartitions(res);
    return v1;
}

Example 30 with Storage

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

the class MixedBinaryInNonZAExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntIntVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        int[] 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]);
                    }
                    int size = v1.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<Int2IntMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Int2IntMap.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.getIntValue()));
        }
    } 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();
        int[] 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++;
    }
    v1.setPartitions(res);
    return v1;
}