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Example 46 with IntFloatVector

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

the class SimpleBinaryOutAllExecutor method apply.

public static Vector apply(IntFloatVector v1, IntIntVector v2, Binary op) {
    IntFloatVector res;
    if (v1.isDense() && v2.isDense()) {
        res = v1.copy();
        float[] resValues = res.getStorage().getValues();
        int[] v2Values = v2.getStorage().getValues();
        for (int idx = 0; idx < resValues.length; idx++) {
            resValues[idx] = op.apply(resValues[idx], v2Values[idx]);
        }
    } else if (v1.isDense() && v2.isSparse()) {
        res = v1.copy();
        float[] resValues = res.getStorage().getValues();
        if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
            for (int i = 0; i < resValues.length; i++) {
                resValues[i] = op.apply(resValues[i], 0);
            }
            ObjectIterator<Int2IntMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2IntMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                resValues[idx] = op.apply(v1.get(idx), entry.getIntValue());
            }
        } else {
            IntIntVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < resValues.length; i++) {
                if (v2Storage.hasKey(i)) {
                    resValues[i] = op.apply(resValues[i], v2.get(i));
                } else {
                    resValues[i] = op.apply(resValues[i], 0);
                }
            }
        }
    } else if (v1.isDense() && v2.isSorted()) {
        res = v1.copy();
        float[] resValues = res.getStorage().getValues();
        if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
            int[] v2Indices = v2.getStorage().getIndices();
            int[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < resValues.length; i++) {
                resValues[i] = op.apply(resValues[i], 0);
            }
            int size = v2.size();
            for (int i = 0; i < size; i++) {
                int idx = v2Indices[i];
                resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
            }
        } else {
            IntIntVectorStorage v2Storage = v2.getStorage();
            for (int i = 0; i < resValues.length; i++) {
                if (v2Storage.hasKey(i)) {
                    resValues[i] = op.apply(resValues[i], v2.get(i));
                } else {
                    resValues[i] = op.apply(resValues[i], 0);
                }
            }
        }
    } else if (v1.isSparse() && v2.isDense()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntFloatVectorStorage newStorage = v1.getStorage().emptyDense();
            float[] resValues = newStorage.getValues();
            int[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                ObjectIterator<Int2FloatMap.Entry> iter = v1.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    resValues[idx] = op.apply(entry.getFloatValue(), v2Values[idx]);
                }
            } else {
                for (int i = 0; i < resValues.length; i++) {
                    if (v1.getStorage().hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
            res = new IntFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSorted() && v2.isDense()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntFloatVectorStorage newStorage = v1.getStorage().emptyDense();
            float[] resValues = newStorage.getValues();
            int[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                int[] v1Indices = v1.getStorage().getIndices();
                float[] v1Values = v1.getStorage().getValues();
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
                }
            } else {
                IntFloatVectorStorage v1Storage = v1.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v1Storage.hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
            res = new IntFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else if (v1.isSparse() && v2.isSparse()) {
        if (op.isKeepStorage()) {
            throw new AngelException("operation is not support!");
        } else {
            IntFloatVectorStorage newStorage = v1.getStorage().emptyDense();
            float[] resValues = newStorage.getValues();
            ObjectIterator<Int2FloatMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2FloatMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                resValues[idx] = entry.getFloatValue();
            }
            if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(resValues[i], 0);
                }
                ObjectIterator<Int2IntMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2IntMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    if (v1.getStorage().hasKey(idx)) {
                        resValues[idx] = op.apply(v1.get(idx), entry.getIntValue());
                    }
                }
            } else {
                IntIntVectorStorage v2Storage = v2.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v2Storage.hasKey(i)) {
                        resValues[i] = op.apply(resValues[i], v2.get(i));
                    } else {
                        resValues[i] = op.apply(resValues[i], 0);
                    }
                }
            }
            res = new IntFloatVector(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 {
            IntFloatVectorStorage newStorage = v1.getStorage().emptyDense();
            float[] resValues = newStorage.getValues();
            ObjectIterator<Int2FloatMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2FloatMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                resValues[idx] = entry.getFloatValue();
            }
            if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
                int[] v2Indices = v2.getStorage().getIndices();
                int[] v2Values = v2.getStorage().getValues();
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(resValues[i], 0);
                }
                int size = v2.size();
                for (int i = 0; i < size; i++) {
                    int idx = v2Indices[i];
                    if (v1.getStorage().hasKey(idx)) {
                        resValues[idx] = op.apply(v1.get(idx), v2Values[i]);
                    }
                }
            } else {
                IntIntVectorStorage v2Storage = v2.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v2Storage.hasKey(i)) {
                        resValues[i] = op.apply(resValues[i], v2.get(i));
                    } else {
                        resValues[i] = op.apply(resValues[i], 0);
                    }
                }
            }
            res = new IntFloatVector(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 {
            IntFloatVectorStorage newStorage = v1.getStorage().emptyDense();
            float[] resValues = newStorage.getValues();
            int[] v1Indices = v1.getStorage().getIndices();
            float[] v1Values = v1.getStorage().getValues();
            int size = v1.size();
            for (int i = 0; i < size; i++) {
                int idx = v1Indices[i];
                resValues[idx] = v1Values[i];
            }
            if (v2.size() < Constant.denseLoopThreshold * v2.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(resValues[i], 0);
                }
                ObjectIterator<Int2IntMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2IntMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    if (v1.getStorage().hasKey(idx)) {
                        resValues[idx] = op.apply(v1.get(idx), entry.getIntValue());
                    }
                }
            } else {
                IntIntVectorStorage v2Storage = v2.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v2Storage.hasKey(i)) {
                        resValues[i] = op.apply(resValues[i], v2.get(i));
                    } else {
                        resValues[i] = op.apply(resValues[i], 0);
                    }
                }
            }
            res = new IntFloatVector(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 {
            IntFloatVectorStorage newStorage = v1.getStorage().emptyDense();
            float[] resValues = newStorage.getValues();
            int v1Pointor = 0;
            int v2Pointor = 0;
            int size1 = v1.size();
            int size2 = v2.size();
            int[] v1Indices = v1.getStorage().getIndices();
            float[] v1Values = v1.getStorage().getValues();
            int[] v2Indices = v2.getStorage().getIndices();
            int[] v2Values = v2.getStorage().getValues();
            if (!op.isCompare()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = Float.NaN;
                }
            }
            while (v1Pointor < size1 && v2Pointor < size2) {
                if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                    resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                    v1Pointor++;
                    v2Pointor++;
                } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                    resValues[v1Indices[v1Pointor]] = op.apply(v1Values[v1Pointor], 0);
                    v1Pointor++;
                } else {
                    // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                    resValues[v2Indices[v2Pointor]] = op.apply(0, v2Values[v2Pointor]);
                    v2Pointor++;
                }
            }
            res = new IntFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return res;
}
Also used : AngelException(com.tencent.angel.exception.AngelException) IntFloatVector(com.tencent.angel.ml.math2.vector.IntFloatVector) ObjectIterator(it.unimi.dsi.fastutil.objects.ObjectIterator) IntIntVectorStorage(com.tencent.angel.ml.math2.storage.IntIntVectorStorage) IntFloatVectorStorage(com.tencent.angel.ml.math2.storage.IntFloatVectorStorage) Int2FloatMap(it.unimi.dsi.fastutil.ints.Int2FloatMap) Int2IntMap(it.unimi.dsi.fastutil.ints.Int2IntMap)

Example 47 with IntFloatVector

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

the class SimpleBinaryOutNonZAExecutor method apply.

public static Vector apply(IntFloatVector v1, IntDummyVector v2, Binary op) {
    IntFloatVectorStorage newStorage = (IntFloatVectorStorage) StorageSwitch.apply(v1, v2, op);
    if (v1.isDense()) {
        float[] resValues = newStorage.getValues();
        int[] v2Indices = v2.getIndices();
        for (int idx : v2Indices) {
            resValues[idx] = op.apply(resValues[idx], 1);
        }
    } else if (v1.isSparse()) {
        int[] v2Indices = v2.getIndices();
        if (((v1.size() + v2.size()) * Constant.intersectionCoeff > Constant.sparseDenseStorageThreshold * v1.getDim())) {
            float[] resValues = newStorage.getValues();
            ObjectIterator<Int2FloatMap.Entry> iter = v1.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2FloatMap.Entry entry = iter.next();
                newStorage.set(entry.getIntKey(), entry.getFloatValue());
            }
            for (int idx : v2Indices) {
                newStorage.set(idx, op.apply(v1.get(idx), 1));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() < 1.5 * capacity) {
                int size = v2.size();
                for (int i = 0; i < size; i++) {
                    int idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), 1));
                }
            } else {
                ObjectIterator<Int2FloatMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Int2FloatMap.Entry entry = iter1.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, entry.getFloatValue());
                }
                int size = v2.size();
                for (int i = 0; i < size; i++) {
                    int idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), 1));
                }
            }
        }
    } else {
        // sorted
        int[] v1Indices = v1.getStorage().getIndices();
        int[] v2Indices = v2.getIndices();
        if (!op.isKeepStorage() && ((v1.size() + v2.size()) * Constant.intersectionCoeff > Constant.sortedDenseStorageThreshold * v1.getDim())) {
            float[] v1Values = v1.getStorage().getValues();
            int size = v1.size();
            for (int i = 0; i < size; i++) {
                newStorage.set(v1Indices[i], v1Values[i]);
            }
            size = v2.size();
            for (int i = 0; i < size; i++) {
                int idx = v2Indices[i];
                newStorage.set(idx, op.apply(newStorage.get(idx), 1));
            }
        } else {
            int v1Pointor = 0;
            int v2Pointor = 0;
            int size1 = v1.size();
            int size2 = v2.size();
            float[] v1Values = v1.getStorage().getValues();
            while (v1Pointor < size1 || v2Pointor < size2) {
                if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                    newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], 1));
                    v1Pointor++;
                    v2Pointor++;
                } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                    newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                    v1Pointor++;
                } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                    newStorage.set(v2Indices[v2Pointor], op.apply(0, 1));
                    v2Pointor++;
                }
            }
        }
    }
    return new IntFloatVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
Also used : IntFloatVectorStorage(com.tencent.angel.ml.math2.storage.IntFloatVectorStorage) Int2FloatMap(it.unimi.dsi.fastutil.ints.Int2FloatMap) IntFloatVector(com.tencent.angel.ml.math2.vector.IntFloatVector) ObjectIterator(it.unimi.dsi.fastutil.objects.ObjectIterator)

Example 48 with IntFloatVector

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

the class SimpleBinaryOutNonZAExecutor method apply.

public static Vector apply(IntDoubleVector v1, IntFloatVector v2, Binary op) {
    IntDoubleVectorStorage newStorage = (IntDoubleVectorStorage) StorageSwitch.apply(v1, v2, op);
    if (v1.isDense() && v2.isDense()) {
        double[] resValues = newStorage.getValues();
        double[] v1Values = v1.getStorage().getValues();
        float[] v2Values = v2.getStorage().getValues();
        for (int idx = 0; idx < resValues.length; idx++) {
            resValues[idx] = op.apply(v1Values[idx], v2Values[idx]);
        }
    } else if (v1.isDense() && v2.isSparse()) {
        double[] resValues = newStorage.getValues();
        double[] v1Values = v1.getStorage().getValues();
        ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
        while (iter.hasNext()) {
            Int2FloatMap.Entry entry = iter.next();
            int idx = entry.getIntKey();
            resValues[idx] = op.apply(v1Values[idx], entry.getFloatValue());
        }
    } else if (v1.isDense() && v2.isSorted()) {
        double[] resValues = newStorage.getValues();
        double[] v1Values = v1.getStorage().getValues();
        int[] v2Indices = v2.getStorage().getIndices();
        float[] v2Values = v2.getStorage().getValues();
        int size = v2.size();
        for (int i = 0; i < size; i++) {
            int idx = v2Indices[i];
            resValues[idx] = op.apply(v1Values[idx], v2Values[i]);
        }
    } else if (v1.isSparse() && v2.isDense()) {
        if (op.isKeepStorage()) {
            int dim = v1.getDim();
            float[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                for (int i = 0; i < dim; i++) {
                    newStorage.set(i, op.apply(0, v2Values[i]));
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(entry.getDoubleValue(), v2Values[idx]));
                }
            } else {
                for (int i = 0; i < dim; i++) {
                    if (v1.getStorage().hasKey(i)) {
                        newStorage.set(i, op.apply(v1.get(i), v2Values[i]));
                    } else {
                        newStorage.set(i, op.apply(0, v2Values[i]));
                    }
                }
            }
        } else {
            double[] resValues = newStorage.getValues();
            float[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                ObjectIterator<Int2DoubleMap.Entry> iter = v1.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2DoubleMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    resValues[idx] = op.apply(entry.getDoubleValue(), v2Values[idx]);
                }
            } else {
                for (int i = 0; i < resValues.length; i++) {
                    if (v1.getStorage().hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
        }
    } else if (v1.isSorted() && v2.isDense()) {
        if (op.isKeepStorage()) {
            int dim = v1.getDim();
            int[] resIndices = newStorage.getIndices();
            double[] resValues = newStorage.getValues();
            float[] v2Values = v2.getStorage().getValues();
            int[] v1Indices = v1.getStorage().getIndices();
            double[] v1Values = v1.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 = v1Indices[i];
                resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
            }
        } else {
            double[] resValues = newStorage.getValues();
            float[] v2Values = v2.getStorage().getValues();
            if (v1.size() < Constant.denseLoopThreshold * v1.getDim()) {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                for (int i = 0; i < resValues.length; i++) {
                    resValues[i] = op.apply(0, v2Values[i]);
                }
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    resValues[idx] = op.apply(v1Values[i], v2Values[idx]);
                }
            } else {
                IntDoubleVectorStorage v1Storage = v1.getStorage();
                for (int i = 0; i < resValues.length; i++) {
                    if (v1Storage.hasKey(i)) {
                        resValues[i] = op.apply(v1.get(i), v2Values[i]);
                    } else {
                        resValues[i] = op.apply(0, v2Values[i]);
                    }
                }
            }
        }
    } else if (v1.isSparse() && v2.isSparse()) {
        int v1Size = v1.size();
        int v2Size = v2.size();
        if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
            ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
            while (iter.hasNext()) {
                Int2FloatMap.Entry entry = iter.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss dense storage is more efficient
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, entry.getDoubleValue());
            }
            ObjectIterator<Int2FloatMap.Entry> iter2 = v2.getStorage().entryIterator();
            while (iter2.hasNext()) {
                Int2FloatMap.Entry entry = iter2.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() <= 1.5 * capacity) {
                // no rehashor one onle rehash is required, nothing to optimization
                ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
                }
            } else {
                // multi-rehash
                ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Int2DoubleMap.Entry entry = iter1.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, entry.getDoubleValue());
                }
                ObjectIterator<Int2FloatMap.Entry> iter2 = v2.getStorage().entryIterator();
                while (iter2.hasNext()) {
                    Int2FloatMap.Entry entry = iter2.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(v1.get(idx), entry.getFloatValue()));
                }
            }
        }
    } else if (v1.isSparse() && v2.isSorted()) {
        int v1Size = v1.size();
        int v2Size = v2.size();
        if (v1Size >= v2Size * Constant.sparseThreshold && (v1Size + v2Size) * Constant.intersectionCoeff <= Constant.sparseDenseStorageThreshold * v1.dim()) {
            // we gauss the indices of v2 maybe is a subset of v1, or overlap is very large
            int[] v2Indices = v2.getStorage().getIndices();
            float[] v2Values = v2.getStorage().getValues();
            for (int i = 0; i < v2.size(); i++) {
                int idx = v2Indices[i];
                newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
            }
        } else if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sparseDenseStorageThreshold * v1.dim()) {
            ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
            while (iter1.hasNext()) {
                Int2DoubleMap.Entry entry = iter1.next();
                int idx = entry.getIntKey();
                newStorage.set(idx, entry.getDoubleValue());
            }
            int[] v2Indices = v2.getStorage().getIndices();
            float[] v2Values = v2.getStorage().getValues();
            int size = v2.size();
            for (int i = 0; i < size; i++) {
                int idx = v2Indices[i];
                newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
            }
        } else {
            // to avoid multi-rehash
            int capacity = 1 << (32 - Integer.numberOfLeadingZeros((int) (v1.size() / 0.75)));
            if (v1.size() + v2.size() <= 1.5 * capacity) {
                int[] v2Indices = v2.getStorage().getIndices();
                float[] v2Values = v2.getStorage().getValues();
                for (int i = 0; i < v2.size(); i++) {
                    int idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            } else {
                ObjectIterator<Int2DoubleMap.Entry> iter1 = v1.getStorage().entryIterator();
                while (iter1.hasNext()) {
                    Int2DoubleMap.Entry entry = iter1.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, entry.getDoubleValue());
                }
                int[] v2Indices = v2.getStorage().getIndices();
                float[] v2Values = v2.getStorage().getValues();
                int size = v2.size();
                for (int i = 0; i < size; i++) {
                    int idx = v2Indices[i];
                    newStorage.set(idx, op.apply(v1.get(idx), v2Values[i]));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSparse()) {
        int v1Size = v1.size();
        int v2Size = v2.size();
        if ((v1Size + v2Size) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                int[] v1Indices = v1.getStorage().getIndices();
                int[] idxiter = v2.getStorage().indexIterator().toIntArray();
                int[] indices = new int[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                IntAVLTreeSet avl = new IntAVLTreeSet(indices);
                IntBidirectionalIterator iter = avl.iterator();
                double[] values = new double[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    int idx = iter.nextInt();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new IntDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getFloatValue()));
                }
            }
        } else {
            if (op.isKeepStorage()) {
                int[] v1Indices = v1.getStorage().getIndices();
                int[] idxiter = v2.getStorage().indexIterator().toIntArray();
                int[] indices = new int[(int) (v1Size + v2Size)];
                System.arraycopy(v1Indices, 0, indices, 0, (int) v1.size());
                System.arraycopy(idxiter, 0, indices, (int) v1.size(), (int) v2.size());
                IntAVLTreeSet avl = new IntAVLTreeSet(indices);
                IntBidirectionalIterator iter = avl.iterator();
                double[] values = new double[indices.length];
                int i = 0;
                while (iter.hasNext()) {
                    int idx = iter.nextInt();
                    indices[i] = idx;
                    values[i] = op.apply(v1.get(idx), v2.get(idx));
                    i++;
                }
                while (i < indices.length) {
                    indices[i] = 0;
                    i++;
                }
                newStorage = new IntDoubleSortedVectorStorage(v1.getDim(), (int) avl.size(), indices, values);
            } else {
                int[] v1Indices = v1.getStorage().getIndices();
                double[] v1Values = v1.getStorage().getValues();
                int size = v1.size();
                for (int i = 0; i < size; i++) {
                    int idx = v1Indices[i];
                    newStorage.set(idx, v1Values[i]);
                }
                ObjectIterator<Int2FloatMap.Entry> iter = v2.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int idx = entry.getIntKey();
                    newStorage.set(idx, op.apply(newStorage.get(idx), entry.getFloatValue()));
                }
            }
        }
    } else if (v1.isSorted() && v2.isSorted()) {
        int v1Pointor = 0;
        int v2Pointor = 0;
        int size1 = v1.size();
        int size2 = v2.size();
        int[] v1Indices = v1.getStorage().getIndices();
        double[] v1Values = v1.getStorage().getValues();
        int[] v2Indices = v2.getStorage().getIndices();
        float[] v2Values = v2.getStorage().getValues();
        if ((size1 + size2) * Constant.intersectionCoeff >= Constant.sortedDenseStorageThreshold * v1.dim()) {
            if (op.isKeepStorage()) {
                // sorted
                int[] resIndices = newStorage.getIndices();
                double[] resValues = newStorage.getValues();
                int global = 0;
                while (v1Pointor < size1 && v2Pointor < size2) {
                    if (v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        resIndices[global] = v1Indices[v1Pointor];
                        resValues[global] = op.apply(v1Values[v1Pointor], v2Values[v2Pointor]);
                        global++;
                        v1Pointor++;
                        v2Pointor++;
                    } else if (v1Indices[v1Pointor] < v2Indices[v2Pointor]) {
                        resIndices[global] = v1Indices[v1Pointor];
                        resValues[global] = v1Values[v1Pointor];
                        global++;
                        v1Pointor++;
                    } else {
                        // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                        resIndices[global] = v2Indices[v2Pointor];
                        resValues[global] = op.apply(0, v2Values[v2Pointor]);
                        global++;
                        v2Pointor++;
                    }
                }
            } else {
                // dense
                while (v1Pointor < size1 || v2Pointor < size2) {
                    if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
                        v1Pointor++;
                        v2Pointor++;
                    } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                        newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                        v1Pointor++;
                    } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                        newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
                        v2Pointor++;
                    }
                }
            }
        } else {
            if (op.isKeepStorage()) {
                int[] resIndices = newStorage.getIndices();
                double[] resValues = newStorage.getValues();
                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] = v1Values[v1Pointor];
                        v1Pointor++;
                        globalPointor++;
                    } else {
                        // v1Indices[v1Pointor] > v2Indices[v2Pointor]
                        resIndices[globalPointor] = v2Indices[v2Pointor];
                        resValues[globalPointor] = op.apply(0, v2Values[v2Pointor]);
                        v2Pointor++;
                        globalPointor++;
                    }
                }
            } else {
                while (v1Pointor < size1 || v2Pointor < size2) {
                    if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] == v2Indices[v2Pointor]) {
                        newStorage.set(v1Indices[v1Pointor], op.apply(v1Values[v1Pointor], v2Values[v2Pointor]));
                        v1Pointor++;
                        v2Pointor++;
                    } else if ((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] < v2Indices[v2Pointor] || (v1Pointor < size1 && v2Pointor >= size2)) {
                        newStorage.set(v1Indices[v1Pointor], v1Values[v1Pointor]);
                        v1Pointor++;
                    } else if (((v1Pointor < size1 && v2Pointor < size2) && v1Indices[v1Pointor] >= v2Indices[v2Pointor]) || (v1Pointor >= size1 && v2Pointor < size2)) {
                        newStorage.set(v2Indices[v2Pointor], op.apply(0, v2Values[v2Pointor]));
                        v2Pointor++;
                    }
                }
            }
        }
    } else {
        throw new AngelException("The operation is not support!");
    }
    return new IntDoubleVector(v1.getMatrixId(), v1.getRowId(), v1.getClock(), v1.getDim(), newStorage);
}
Also used : AngelException(com.tencent.angel.exception.AngelException) Int2DoubleMap(it.unimi.dsi.fastutil.ints.Int2DoubleMap) IntBidirectionalIterator(it.unimi.dsi.fastutil.ints.IntBidirectionalIterator) ObjectIterator(it.unimi.dsi.fastutil.objects.ObjectIterator) IntDoubleVector(com.tencent.angel.ml.math2.vector.IntDoubleVector) IntDoubleVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage) Int2FloatMap(it.unimi.dsi.fastutil.ints.Int2FloatMap) IntAVLTreeSet(it.unimi.dsi.fastutil.ints.IntAVLTreeSet) IntDoubleSortedVectorStorage(com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage)

Example 49 with IntFloatVector

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

the class GetNodeFeats method partitionGet.

@Override
public PartitionGetResult partitionGet(PartitionGetParam partParam) {
    PartGetNodeFeatsParam param = (PartGetNodeFeatsParam) partParam;
    ServerMatrix matrix = psContext.getMatrixStorageManager().getMatrix(partParam.getMatrixId());
    ServerPartition part = matrix.getPartition(partParam.getPartKey().getPartitionId());
    ServerLongAnyRow row = (ServerLongAnyRow) (((RowBasedPartition) part).getRow(0));
    long[] nodeIds = param.getNodeIds();
    IntFloatVector[] feats = new IntFloatVector[nodeIds.length];
    for (int i = 0; i < nodeIds.length; i++) {
        if (row.get(nodeIds[i]) == null) {
            continue;
        }
        feats[i] = ((Node) (row.get(nodeIds[i]))).getFeats();
    }
    return new PartGetNodeFeatsResult(part.getPartitionKey().getPartitionId(), feats);
}
Also used : ServerMatrix(com.tencent.angel.ps.storage.matrix.ServerMatrix) RowBasedPartition(com.tencent.angel.ps.storage.partition.RowBasedPartition) ServerLongAnyRow(com.tencent.angel.ps.storage.vector.ServerLongAnyRow) ServerPartition(com.tencent.angel.ps.storage.partition.ServerPartition) IntFloatVector(com.tencent.angel.ml.math2.vector.IntFloatVector)

Example 50 with IntFloatVector

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

the class GetNodeFeats method merge.

@Override
public GetResult merge(List<PartitionGetResult> partResults) {
    Int2ObjectArrayMap<PartitionGetResult> partIdToResultMap = new Int2ObjectArrayMap<>(partResults.size());
    for (PartitionGetResult result : partResults) {
        partIdToResultMap.put(((PartGetNodeFeatsResult) result).getPartId(), result);
    }
    GetNodeFeatsParam param = (GetNodeFeatsParam) getParam();
    long[] nodeIds = param.getNodeIds();
    List<PartitionGetParam> partParams = param.getPartParams();
    Long2ObjectOpenHashMap<IntFloatVector> results = new Long2ObjectOpenHashMap<>(nodeIds.length);
    int size = partResults.size();
    for (int i = 0; i < size; i++) {
        PartGetNodeFeatsParam partParam = (PartGetNodeFeatsParam) partParams.get(i);
        PartGetNodeFeatsResult partResult = (PartGetNodeFeatsResult) partIdToResultMap.get(partParam.getPartKey().getPartitionId());
        int start = partParam.getStartIndex();
        int end = partParam.getEndIndex();
        IntFloatVector[] feats = partResult.getFeats();
        for (int j = start; j < end; j++) {
            if (feats[j - start] != null) {
                results.put(nodeIds[j], feats[j - start]);
            }
        }
    }
    return new GetNodeFeatsResult(results);
}
Also used : Int2ObjectArrayMap(it.unimi.dsi.fastutil.ints.Int2ObjectArrayMap) PartitionGetParam(com.tencent.angel.ml.matrix.psf.get.base.PartitionGetParam) Long2ObjectOpenHashMap(it.unimi.dsi.fastutil.longs.Long2ObjectOpenHashMap) IntFloatVector(com.tencent.angel.ml.math2.vector.IntFloatVector) PartitionGetResult(com.tencent.angel.ml.matrix.psf.get.base.PartitionGetResult)

Aggregations

IntFloatVector (com.tencent.angel.ml.math2.vector.IntFloatVector)104 ObjectIterator (it.unimi.dsi.fastutil.objects.ObjectIterator)60 Int2FloatMap (it.unimi.dsi.fastutil.ints.Int2FloatMap)57 IntFloatVectorStorage (com.tencent.angel.ml.math2.storage.IntFloatVectorStorage)50 CompIntFloatVector (com.tencent.angel.ml.math2.vector.CompIntFloatVector)34 IntDoubleVectorStorage (com.tencent.angel.ml.math2.storage.IntDoubleVectorStorage)33 IntIntVectorStorage (com.tencent.angel.ml.math2.storage.IntIntVectorStorage)32 IntLongVectorStorage (com.tencent.angel.ml.math2.storage.IntLongVectorStorage)32 IntFloatSparseVectorStorage (com.tencent.angel.ml.math2.storage.IntFloatSparseVectorStorage)31 LongDoubleVectorStorage (com.tencent.angel.ml.math2.storage.LongDoubleVectorStorage)30 LongFloatVectorStorage (com.tencent.angel.ml.math2.storage.LongFloatVectorStorage)30 LongIntVectorStorage (com.tencent.angel.ml.math2.storage.LongIntVectorStorage)30 LongLongVectorStorage (com.tencent.angel.ml.math2.storage.LongLongVectorStorage)30 Storage (com.tencent.angel.ml.math2.storage.Storage)30 IntFloatSortedVectorStorage (com.tencent.angel.ml.math2.storage.IntFloatSortedVectorStorage)25 IntDoubleSortedVectorStorage (com.tencent.angel.ml.math2.storage.IntDoubleSortedVectorStorage)21 AngelException (com.tencent.angel.exception.AngelException)20 IntDoubleSparseVectorStorage (com.tencent.angel.ml.math2.storage.IntDoubleSparseVectorStorage)20 IntIntSortedVectorStorage (com.tencent.angel.ml.math2.storage.IntIntSortedVectorStorage)20 IntIntSparseVectorStorage (com.tencent.angel.ml.math2.storage.IntIntSparseVectorStorage)20