Что требуется для создания адаптера std::vector на основе xtensor с формами и шагами?

Я сейчас создаю пример xtensor «структуры, включающие форму и шаги», чтобы использовать его для класса изображения с собственной информацией заголовка. Я дошел до этого:

#include <xtensor/xadapt.hpp>
#include <xtensor/xstrides.hpp>

// see https://github.com/xtensor-stack/xtensor/blob/master/docs/source/external-structures.rst
template <class T>
struct raw_tensor {
    using container_type = std::vector<T>;
    using shape_type = std::vector<std::size_t>;
    container_type 
        m_data;
    shape_type 
        m_shape,
        m_strides,
        m_backstrides;
    static constexpr xt::layout_type 
        layout = xt::layout_type::dynamic;
};

template <class T>
class raw_tensor_adaptor;

template <class T>
struct xt::xcontainer_inner_types<raw_tensor_adaptor<T>> {
    using container_type = typename raw_tensor<T>::container_type;
    using inner_shape_type = typename raw_tensor<T>::shape_type;
    using inner_strides_type = inner_shape_type;
    using inner_backstrides_type = inner_shape_type;
    using shape_type = inner_shape_type;
    using strides_type = inner_shape_type;
    using backstrides_type = inner_shape_type;
    static constexpr layout_type layout = raw_tensor<T>::layout;
};

template <class T>
struct xt::xiterable_inner_types<raw_tensor_adaptor<T>>
    : xcontainer_iterable_types<raw_tensor_adaptor<T>> {
};

template <class T>
class raw_tensor_adaptor : public xt::xcontainer<raw_tensor_adaptor<T>>,
                           public xt::xcontainer_semantic<raw_tensor_adaptor<T>> {

public:

    using self_type = raw_tensor_adaptor<T>;
    using base_type = xt::xcontainer<self_type>;
    using semantic_base = xt::xcontainer_semantic<self_type>;

    raw_tensor_adaptor(const raw_tensor_adaptor&) = default;
    raw_tensor_adaptor& operator=(const raw_tensor_adaptor&) = default;    
    raw_tensor_adaptor(raw_tensor_adaptor&&) = default;
    raw_tensor_adaptor& operator=(raw_tensor_adaptor&&) = default;

    template <class E>
    raw_tensor_adaptor(const xt::xexpression<E>& e) : base_type() {
        semantic_base::assign(e);
    }

    template <class E>
    self_type& operator=(const xt::xexpression<E>& e) {
        return semantic_base::operator=(e);
    }   
    
};

int main() {

raw_tensor<double> i,j,k;       // this works
using tensor_type = raw_tensor_adaptor<double>;
// tensor_type a, b, c;         // but not this if un-commented
//   .... init a, b, c
// tensor_type d = a + b - c;   raw_tensor < int > a;
return 0;
    
}

При использовании функции main(), которая просто объявляет объекты класса raw_tensor<double>, компиляция завершается без ошибок.

В Linux (с gcc-11) я могу (повторно) запустить этот пример, выполнив:

$ cd /tmp && mkdir -p xtensor-test && cd xtensor-test
$ git clone https://github.com/xtensor-stack/xtensor.git
$ git clone https://github.com/xtensor-stack/xtl.git
$ vi xtensor-test.cpp # insert the code block above and save
$ g++ -o xtensor-test xtensor-test.cpp -Ixtensor/include -Ixtl/include

Однако я не могу сделать следующее:

1. добавьте методы resize() или аксессора: когда я добавляю функции resize() (без параметра шаблона T) внутри класса, это не работает, поскольку внутренние типы и члены shape_type, m_shape и т. д. неизвестны. Но это единственное место, где можно перегрузиться resize(), правда?
2. добавьте строки с веб-страницы, которые объявляют объекты адаптера:
   using tensor_type = raw_tensor_adaptor<double>;
tensor_type a, b, c;

Когда я объявляю эти адаптеры, строка a, b, c генерирует следующие ошибки:

include/xtensor/xiterable.hpp:288:19: error: no type named 'xexpression_type' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >’
include/xtensor/xaccessible.hpp:35:15: error: no type named 'reference' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >’
include/xtensor/xaccessible.hpp:36:15: error: no type named 'const_reference' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >’
include/xtensor/xaccessible.hpp:37:15: error: no type named 'size_type' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >’
include/xtensor/xaccessible.hpp:47:48: error: no type named 'const_reference' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >’
include/xtensor/xaccessible.hpp:111:26: error: 'at' has not been declared in 'using base_type = class 
include/xtensor/xaccessible.hpp:112:35: error: 'operator[]' has not been declared in 'using base_type = class xt::xconst_accessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xconst_accessible<raw_tensor_adaptor<double> >’}
include/xtensor/xaccessible.hpp:113:26: error: 'back' has not been declared in 'using base_type = class xt::xconst_accessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xconst_accessible<raw_tensor_adaptor<double> >’}
include/xtensor/xaccessible.hpp:114:26: error: 'front' has not been declared in 'using base_type = class xt::xconst_accessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xconst_accessible<raw_tensor_adaptor<double> >’}
include/xtensor/xaccessible.hpp:115:26: error: 'periodic' has not been declared in 'using base_type = class xt::xconst_accessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xconst_accessible<raw_tensor_adaptor<double> >’}
include/xtensor/xcontainer.hpp:79:15: error: no type named 'storage_type' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >'
include/xtensor/xcontainer.hpp:80:15: error: no type named 'storage_type' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >'
include/xtensor/xcontainer.hpp:82:15: error: no type named 'reference' in 'struct  xt::xcontainer_inner_types<raw_tensor_adaptor<double> >'
include/xtensor/xcontainer.hpp:83:15: error: no type named 'const_reference' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >'
include/xtensor/xcontainer.hpp:86:15: error: no type named 'size_type' in 'struct  xt::xcontainer_inner_types<raw_tensor_adaptor<double> >'
include/xtensor/xcontainer.hpp:88:15: error: no type named 'storage_type' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >'
include/xtensor/xcontainer.hpp:89:15: error: no type named 'storage_type' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >'
include/xtensor/xcontainer.hpp:107:15: error: no type named 'storage_type' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >'
include/xtensor/xcontainer.hpp:108:15: error: no type named 'storage_type' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >'
include/xtensor/xcontainer.hpp:140:32: error: 'at' has not been declared in 'using accessible_base = class xt::xaccessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xaccessible<raw_tensor_adaptor<double> >’}
include/xtensor/xcontainer.hpp:141:32: error: 'shape' has not been declared in 'using accessible_base = class xt::xaccessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xaccessible<raw_tensor_adaptor<double> >’}
include/xtensor/xcontainer.hpp:142:41: error: 'operator[]' has not been declared in 'using accessible_base = class xt::xaccessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xaccessible<raw_tensor_adaptor<double> >’}
include/xtensor/xcontainer.hpp:143:32: error: 'back' has not been declared in 'using accessible_base = class xt::xaccessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xaccessible<raw_tensor_adaptor<double> >’}
include/xtensor/xcontainer.hpp:144:32: error: 'front' has not been declared in 'using accessible_base = class xt::xaccessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xaccessible<raw_tensor_adaptor<double> >’}
include/xtensor/xcontainer.hpp:146:32: error: 'periodic' has not been declared in 'using accessible_base = class xt::xaccessible<raw_tensor_adaptor<double> >’ {aka ‘class xt::xaccessible<raw_tensor_adaptor<double> >’}
include/xtensor/xcontainer.hpp:182:15: error: no type named 'storage_type' in 'struct
include/xtensor/xsemantic.hpp:64:15: error: no type named 'temporary_type' in 'struct xt::xcontainer_inner_types<raw_tensor_adaptor<double> >’

из заголовков xtensor и

xtensor-test.cpp:70:13: error: no matching function for call to ‘raw_tensor_adaptor<double>::raw_tensor_adaptor()’
 tensor_type a, b, c;            // but not this if un-commented
             ^
xtensor-test.cpp:55:5: note: candidate: ‘template<class E> raw_tensor_adaptor<T>::raw_tensor_adaptor(const xt::xexpression<E>&)’
     raw_tensor_adaptor(const xt::xexpression<E>& e) : base_type() {
     ^~~~~~~~~~~~~~~~~~
xtensor-test.cpp:55:5: note:   template argument deduction/substitution failed:
xtensor-test.cpp:70:13: note:   candidate expects 1 argument, 0 provided
 tensor_type a, b, c;            // but not this if un-commented
             ^
xtensor-test.cpp:51:5: note: candidate: ‘raw_tensor_adaptor<T>::raw_tensor_adaptor(raw_tensor_adaptor<T>&&) [with T = double]’
     raw_tensor_adaptor(raw_tensor_adaptor&&) = default;
     ^~~~~~~~~~~~~~~~~~
xtensor-test.cpp:51:5: note:   candidate expects 1 argument, 0 provided
xtensor-test.cpp:49:5: note: candidate: ‘raw_tensor_adaptor<T>::raw_tensor_adaptor(const raw_tensor_adaptor<T>&) [with T = double]’
     raw_tensor_adaptor(const raw_tensor_adaptor&) = default;
     ^~~~~~~~~~~~~~~~~~
xtensor-test.cpp:49:5: note:   candidate expects 1 argument, 0 provided
xtensor-test.cpp:49:5: note: candidate: ‘raw_tensor_adaptor<T>::raw_tensor_adaptor(const raw_tensor_adaptor<T>&) [with T = double]’
     raw_tensor_adaptor(const raw_tensor_adaptor&) = default;
     ^~~~~~~~~~~~~~~~~~

из файла .cpp

На веб-странице указано определить семантику и реализовать методы и функции, специфичные для структуры raw_tensor. Но у меня такое ощущение, что я делаю это не в том месте.

Есть ли у кого-нибудь этот пример для работы с экземпляром raw_tensor_adaptor? Большое спасибо!