Function CopyTensorInfoImpl

src/data/data.cc:489–517

namespace {
template <int32_t D, typename T>
void CopyTensorInfoImpl(Context const* ctx, Json arr_interface, linalg::Tensor<T, D>* p_out) {
  ArrayInterface<D> array{arr_interface};
  if (array.n == 0) {
    p_out->Reshape(array.shape);
    return;
  }
  CHECK_EQ(array.valid.Capacity(), 0)
      << "Meta info like label or weight can not have missing value.";
  if (array.is_contiguous && array.type == ToDType<T>::kType) {
    // Handle contigious
    p_out->ModifyInplace([&](HostDeviceVector<T>* data, common::Span<size_t, D> shape) {
      // set shape
      std::copy(array.shape, array.shape + D, shape.data());
      // set data
      data->Resize(array.n);
      std::memcpy(data->HostPointer(), array.data, array.n * sizeof(T));
    });
    return;
  }
  p_out->Reshape(array.shape);
  auto t_out = p_out->View(DeviceOrd::CPU());
  CHECK(t_out.CContiguous());
  auto const shape = t_out.Shape();
  DispatchDType(array, DeviceOrd::CPU(), [&](auto&& in) {
    linalg::cpu_impl::TransformIdxKernel(t_out, ctx->Threads(), [&](auto i, auto) {
      return std::apply(in, linalg::UnravelIndex<D>(i, shape));
    });
  });
}

void ReshapeInfo(bst_idx_t n_samples, linalg::Matrix<float>* p_info, StringView name) {
  if (n_samples != 0 && p_info->Shape(0) != n_samples) {