Examples with ObjectIterator it.unimi.dsi.fastutil.objects.ObjectIterator used on opensource projects

Example 91 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class StreamSerdeUtils method serializeIntFloatVector.

// IntFloatVector
private static void serializeIntFloatVector(DataOutputStream out, IntFloatVector vector) throws IOException {
    IntFloatVectorStorage storage = vector.getStorage();
    if (storage.isDense()) {
        serializeInt(out, DENSE_STORAGE_TYPE);
        serializeFloats(out, storage.getValues());
    } else if (storage.isSparse()) {
        serializeInt(out, SPARSE_STORAGE_TYPE);
        serializeInt(out, storage.size());
        ObjectIterator<Int2FloatMap.Entry> iter = storage.entryIterator();
        while (iter.hasNext()) {
            Int2FloatMap.Entry e = iter.next();
            serializeInt(out, e.getIntKey());
            serializeFloat(out, e.getFloatValue());
        }
    } else if (storage.isSorted()) {
        serializeInt(out, SORTED_STORAGE_TYPE);
        int[] indices = vector.getStorage().getIndices();
        float[] values = vector.getStorage().getValues();
        serializeInts(out, indices);
        serializeFloats(out, values);
    } else {
        throw new UnsupportedOperationException("Unsupport storage type " + vector.getStorage().getClass());
    }
}

Example 92 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class DotMatrixExecutor method apply.

private static Vector apply(BlasFloatMatrix mat, boolean trans, IntLongVector v) {
    int m = mat.getNumRows(), n = mat.getNumCols();
    float[] resArr;
    if (trans) {
        assert m == v.getDim();
        resArr = new float[n];
    } else {
        assert n == v.getDim();
        resArr = new float[m];
    }
    int r = mat.getNumRows(), c = mat.getNumCols();
    float[] data = mat.getData();
    if (v.isDense()) {
        float[] tempArray = ArrayCopy.copy(v.getStorage().getValues(), new float[v.getDim()]);
        if (trans) {
            blas.sgemv("N", c, r, 1.0f, data, c, tempArray, 1, 0.0f, resArr, 1);
        } else {
            blas.sgemv("T", c, r, 1.0f, data, c, tempArray, 1, 0.0f, resArr, 1);
        }
    } else if (v.isSparse()) {
        if (trans) {
            for (int j = 0; j < c; j++) {
                ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int i = entry.getIntKey();
                    resArr[j] += data[i * c + j] * entry.getLongValue();
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                ObjectIterator<Int2LongMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2LongMap.Entry entry = iter.next();
                    int j = entry.getIntKey();
                    resArr[i] += data[i * c + j] * entry.getLongValue();
                }
            }
        }
    } else {
        // sorted
        if (trans) {
            for (int j = 0; j < r; j++) {
                int[] idxs = v.getStorage().getIndices();
                long[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[j] += data[idxs[k] * c + j] * vals[k];
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                int[] idxs = v.getStorage().getIndices();
                long[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[i] += data[i * c + idxs[k]] * vals[k];
                }
            }
        }
    }
    IntFloatDenseVectorStorage storage = new IntFloatDenseVectorStorage(resArr);
    return new IntFloatVector(v.getMatrixId(), v.getClock(), 0, resArr.length, storage);
}

Example 93 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class MixedBinaryInAllExecutor method apply.

private static Vector apply(CompIntDoubleVector v1, IntLongVector v2, Binary op) {
    IntDoubleVector[] parts = v1.getPartitions();
    Storage[] resParts = StorageSwitch.applyComp(v1, v2, op);
    if (v2.isDense()) {
        long[] v2Values = v2.getStorage().getValues();
        int base = 0, k = 0;
        for (IntDoubleVector part : parts) {
            IntDoubleVectorStorage resPart = (IntDoubleVectorStorage) resParts[k];
            if (part.isDense()) {
                double[] partValue = part.getStorage().getValues();
                double[] resPartValues = resPart.getValues();
                for (int i = 0; i < partValue.length; i++) {
                    int idx = i + base;
                    resPartValues[i] = op.apply(partValue[i], v2Values[idx]);
                }
            } else if (part.isSparse()) {
                double[] resPartValues = resPart.getValues();
                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 < resPartValues.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
                int[] resPartIndices = resPart.getIndices();
                double[] resPartValues = resPart.getValues();
                if (op.isKeepStorage()) {
                    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++) {
                            resPartIndices[i] = i;
                            resPartValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            resPartValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < resPartValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                resPartIndices[i] = i;
                                resPartValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                resPartIndices[i] = i;
                                resPartValues[i] = op.apply(0, v2Values[i + 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++) {
                            resPartValues[i] = op.apply(0, v2Values[i + base]);
                        }
                        int size = part.size();
                        for (int i = 0; i < size; i++) {
                            int idx = partIndices[i];
                            resPartValues[idx] = op.apply(partValues[i], v2Values[idx + base]);
                        }
                    } else {
                        IntDoubleVectorStorage partStorage = part.getStorage();
                        for (int i = 0; i < resPartValues.length; i++) {
                            if (partStorage.hasKey(i)) {
                                resPartValues[i] = op.apply(partStorage.get(i), v2Values[i + base]);
                            } else {
                                resPartValues[i] = op.apply(0, v2Values[i + base]);
                            }
                        }
                    }
                }
            }
            base += part.getDim();
            k++;
        }
    } else {
        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();
        for (int i = 0; i < v1.getDim(); i++) {
            int pidx = (int) (i / subDim);
            int subidx = i % subDim;
            if (v2.getStorage().hasKey(i)) {
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), v2.get(i)));
            } else {
                ((IntDoubleVectorStorage) resParts[pidx]).set(subidx, op.apply(parts[pidx].get(subidx), 0));
            }
        }
    }
    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;
}

Example 94 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class DotMatrixExecutor method apply.

private static Vector apply(BlasFloatMatrix mat, boolean trans, IntFloatVector v) {
    int m = mat.getNumRows(), n = mat.getNumCols();
    float[] resArr;
    if (trans) {
        assert m == v.getDim();
        resArr = new float[n];
    } else {
        assert n == v.getDim();
        resArr = new float[m];
    }
    int r = mat.getNumRows(), c = mat.getNumCols();
    float[] data = mat.getData();
    if (v.isDense()) {
        float[] tempArray = v.getStorage().getValues();
        if (trans) {
            blas.sgemv("N", c, r, 1.0f, data, c, tempArray, 1, 0.0f, resArr, 1);
        } else {
            blas.sgemv("T", c, r, 1.0f, data, c, tempArray, 1, 0.0f, resArr, 1);
        }
    } else if (v.isSparse()) {
        if (trans) {
            for (int j = 0; j < c; j++) {
                ObjectIterator<Int2FloatMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int i = entry.getIntKey();
                    resArr[j] += data[i * c + j] * entry.getFloatValue();
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                ObjectIterator<Int2FloatMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2FloatMap.Entry entry = iter.next();
                    int j = entry.getIntKey();
                    resArr[i] += data[i * c + j] * entry.getFloatValue();
                }
            }
        }
    } else {
        // sorted
        if (trans) {
            for (int j = 0; j < r; j++) {
                int[] idxs = v.getStorage().getIndices();
                float[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[j] += data[idxs[k] * c + j] * vals[k];
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                int[] idxs = v.getStorage().getIndices();
                float[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[i] += data[i * c + idxs[k]] * vals[k];
                }
            }
        }
    }
    IntFloatDenseVectorStorage storage = new IntFloatDenseVectorStorage(resArr);
    return new IntFloatVector(v.getMatrixId(), v.getClock(), 0, resArr.length, storage);
}

Example 95 with ObjectIterator

use of it.unimi.dsi.fastutil.objects.ObjectIterator in project angel by Tencent.

the class DotMatrixExecutor method apply.

private static Vector apply(BlasDoubleMatrix mat, boolean trans, IntIntVector v) {
    int m = mat.getNumRows(), n = mat.getNumCols();
    double[] resArr;
    if (trans) {
        assert m == v.getDim();
        resArr = new double[n];
    } else {
        assert n == v.getDim();
        resArr = new double[m];
    }
    int r = mat.getNumRows(), c = mat.getNumCols();
    double[] data = mat.getData();
    if (v.isDense()) {
        double[] tempArray = ArrayCopy.copy(v.getStorage().getValues(), new double[v.getDim()]);
        if (trans) {
            blas.dgemv("N", c, r, 1.0, data, c, tempArray, 1, 0.0, resArr, 1);
        } else {
            blas.dgemv("T", c, r, 1.0, data, c, tempArray, 1, 0.0, resArr, 1);
        }
    } else if (v.isSparse()) {
        if (trans) {
            for (int j = 0; j < c; j++) {
                ObjectIterator<Int2IntMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2IntMap.Entry entry = iter.next();
                    int i = entry.getIntKey();
                    resArr[j] += data[i * c + j] * entry.getIntValue();
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                ObjectIterator<Int2IntMap.Entry> iter = v.getStorage().entryIterator();
                while (iter.hasNext()) {
                    Int2IntMap.Entry entry = iter.next();
                    int j = entry.getIntKey();
                    resArr[i] += data[i * c + j] * entry.getIntValue();
                }
            }
        }
    } else {
        // sorted
        if (trans) {
            for (int j = 0; j < r; j++) {
                int[] idxs = v.getStorage().getIndices();
                int[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[j] += data[idxs[k] * c + j] * vals[k];
                }
            }
        } else {
            for (int i = 0; i < r; i++) {
                int[] idxs = v.getStorage().getIndices();
                int[] vals = v.getStorage().getValues();
                for (int k = 0; k < idxs.length; k++) {
                    resArr[i] += data[i * c + idxs[k]] * vals[k];
                }
            }
        }
    }
    IntDoubleDenseVectorStorage storage = new IntDoubleDenseVectorStorage(resArr);
    return new IntDoubleVector(v.getMatrixId(), v.getClock(), 0, resArr.length, storage);
}