AscendIndexSQ

小库算法AscendIndexSQ可以根据一组数据进行训练并生成合适的量化函数，对于输入的float32的特征向量，AscendIndexSQ对其量化为Int8类型的特征向量并存储在Device侧以进一步压缩存储空间，在执行向量比对时，将Int8类型的向量反量化为原始的特征向量执行后续的计算，典型AscendIndexSQ的样例参考如下。

#include <faiss/ascend/AscendIndexSQ.h>
#include <iostream>

using namespace std;

int main(int argc, char **argv)
{
    const size_t dim = 512;
    const size_t ntotal = 10000;
    vector<float> data(dim * ntotal);
    for (size_t i = 0; i < data.size(); i++) {
        data[i] = drand48();
    }

    const size_t k = 100;
    const size_t searchNum  = 100;
    vector<float> dist(k * searchNum);
    vector<long> indices(k * searchNum);

    cout << "Search data set successfully." << endl;

    faiss::ascend::AscendIndexSQ *index = nullptr;
    try {
        faiss::ascend::AscendIndexSQConfig chipConf{0};
        index = new faiss::ascend::AscendIndexSQ(dim, faiss::ScalarQuantizer::QuantizerType::QT_8bit, faiss::METRIC_L2, chipConf);
        index->train(ntotal, data.data());
        index->add(ntotal, data.data());
        index->search(searchNum, data.data(), k, dist.data(), indices.data());
    } catch (...) {
        cout << "Exception caught!" << endl;
        delete index;
        return -1;
    }
    delete index;
    cout << "Search finished successfully" << endl;
    return 0;
}

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