size_ Class — pytorch Architecture

Source Code

aten/src/ATen/cpu/vec/vec256/vec256_qint.h lines 928–993

template <
    typename T,
    typename float_vec_return_type_,
    typename int_vec_return_type_,
    int size_>
struct VectorizedQuantizedConverter {
  static constexpr int size() {
    return size_;
  }

  static constexpr int float_num_vecs() {
    return size_ / Vectorized<float>::size();
  }

  static constexpr int int_num_vecs() {
    return size_ / Vectorized<int>::size();
  }

  using float_vec_return_type = float_vec_return_type_;
  using int_vec_return_type = int_vec_return_type_;

  using value_type = typename T::underlying;
  std::array<value_type, size_> vals;

  VectorizedQuantizedConverter(T val) {
    for (const auto i : c10::irange(size())) {
      vals[i] = val.val_;
    }
  }

  VectorizedQuantizedConverter(const void* ptr) {
    memcpy(vals.data(), ptr, sizeof(value_type) * size());
  }

  void store(void* ptr, int count = size()) const {
    memcpy(ptr, vals.data(), count * sizeof(value_type));
  }

  float_vec_return_type dequantize(
      Vectorized<float> scale,
      Vectorized<float> zero_point,
      Vectorized<float> /*scale_zp_premul*/) const {
    float_vec_return_type rv;
    for (const auto i : c10::irange(float_num_vecs())) {
      float tmp_vals[Vectorized<float>::size()];
      for (const auto j : c10::irange(Vectorized<float>::size())) {
        tmp_vals[j] = at::native::dequantize_val<T>(
            scale[j],
            zero_point[j],
            T(vals[Vectorized<float>::size() * i + j]));
      }
      rv[i] = Vectorized<float>(tmp_vals);
    }
    return rv;
  }

  float_vec_return_type dequantize(
      Vectorized<float> scale,
      Vectorized<float> zero_point) const {
    Vectorized<float> scale_zp_premul;
    return dequantize(scale, zero_point, scale_zp_premul);
  }

 protected:
  VectorizedQuantizedConverter() = default;
};