VECTOR_T Class — pytorch Architecture

Source Code

aten/src/ATen/native/quantized/cpu/qnnpack/include/pack_block_sparse.h lines 28–76

template <typename T>
struct OwnedOrBorrowedVector {
  using VECTOR_T =
#ifndef _WIN32
      std::vector<T, AlignedAllocator<T, 16>>;
#else
      std::vector<T>;
#endif

  // Only one of owned_vec_data_ or borrowed_tuple_data_ will be meaningfully
  // populated.
  // A union could potentially be used here to reduce memory usage.
  // std::variant is not used here because it causes internal build errors
  // due to incompatibility.
  VECTOR_T owned_vec_data_;
  std::tuple<T*, uint32_t> borrowed_tuple_data_;
  bool owned;

  VECTOR_T& vector() {
    assert(owned);
    return owned_vec_data_;
  }

  uint32_t size() const {
    if (owned) {
      return owned_vec_data_.size();
    } else {
      return std::get<1>(borrowed_tuple_data_);
    }
  }

  const T* data() const {
    if (owned) {
      return owned_vec_data_.data();
    } else {
      return std::get<0>(borrowed_tuple_data_);
    }
  }

  const T& operator[](int i) const {
    return data()[i];
  }

  OwnedOrBorrowedVector() : owned(true) {}

  OwnedOrBorrowedVector(T* data_ptr, const uint32_t size)
      : borrowed_tuple_data_(std::tuple<T*, uint32_t>(data_ptr, size)),
        owned(false) {}
};