Class sparse_tensor_t

include/matx/core/sparse_tensor.h:81–120

          typename StorageP = Storage<POS>,
          typename DimDesc = DefaultDescriptor<TF::DIM>>
class sparse_tensor_t
    : public detail::tensor_impl_t<
          VAL, TF::DIM, DimDesc, detail::SparseTensorData<VAL, CRD, POS, TF>> {
public:
  using sparse_tensor = bool;
  using val_type = VAL;
  using crd_type = CRD;
  using pos_type = POS;
  using Format = TF;

  static constexpr int DIM = TF::DIM;
  static constexpr int LVL = TF::LVL;

  //
  // Constructs a sparse tensor with given shape and contents.
  //
  // The storage format is defined through the template. The contents
  // consist of a buffer for the values (primary storage), and LVL times
  // a buffer with the coordinates and LVL times a buffer with the positions
  // (secondary storage). The semantics of these contents depend on the
  // used storage format.
  //
  // Most users should *not* use this constructor directly, since it depends
  // on intricate knowledge of the storage formats. Instead, users should
  // use the "make_sparse_tensor" methods that provide factory methods in
  // terms of storage formats that are more familiar (COO, CSR, etc).
  //
  __MATX_INLINE__
  sparse_tensor_t(const typename DimDesc::shape_type (&shape)[DIM],
                  StorageV &&vals, StorageC (&&crd)[LVL], StorageP (&&pos)[LVL])
      : detail::tensor_impl_t<VAL, DIM, DimDesc,
                              detail::SparseTensorData<VAL, CRD, POS, TF>>(
            shape) {
    values_ = std::move(vals);
    for (int l = 0; l < LVL; l++) {
      coordinates_[l] = std::move(crd[l]);
      positions_[l] = std::move(pos[l]);
    }
    SetSparseDataImpl();
  }

  // Default destructor.
  __MATX_INLINE__ ~sparse_tensor_t() = default;