Requantization Class — pytorch Architecture

Source Code

aten/src/ATen/native/quantized/cpu/qnnpack/bench/requantization.cc lines 36–83

class Requantization : public benchmark::Fixture {
 public:
  inline Requantization() {
    cpuinfo_initialize();
    const size_t l1d_size = cpuinfo_get_l1d_cache(0)->size;
    const size_t l1d_reserve = 1024;
    n_ = (l1d_size - l1d_reserve) / (sizeof(int32_t) + sizeof(uint8_t));
    n_ = n_ / 16 * 16;
  }

  void SetUp(const benchmark::State&) override {
    const uint_fast32_t seed =
        std::chrono::steady_clock::now().time_since_epoch().count();
    auto rng =
        std::bind(std::uniform_int_distribution<int32_t>(), std::mt19937(seed));

    input_.resize(n());
    std::generate(input_.begin(), input_.end(), std::ref(rng));
    output_.resize(n());
    std::fill(output_.begin(), output_.end(), 0xA5);
  }

  void TearDown(benchmark::State& state) override {
    state.SetItemsProcessed(uint64_t(state.iterations()) * n());
    state.SetBytesProcessed(
        uint64_t(state.iterations()) * n() *
        (sizeof(int32_t) + sizeof(uint8_t)));
    input_.clear();
    output_.clear();
  }

  inline const int32_t* input() const {
    return input_.data();
  }

  inline uint8_t* output() {
    return output_.data();
  }

  inline size_t n() const {
    return n_;
  }

 protected:
  std::vector<int32_t, AlignedAllocator<int32_t, 32>> input_;
  std::vector<uint8_t> output_;
  size_t n_;
};