diff --git a/include/xtensor-python/pyarray.hpp b/include/xtensor-python/pyarray.hpp
index 03e803d..8979fcf 100644
--- a/include/xtensor-python/pyarray.hpp
+++ b/include/xtensor-python/pyarray.hpp
@@ -172,12 +172,12 @@ namespace xt
         void init_array(const shape_type& shape, const strides_type& strides);
         void init_from_python();
 
-        const inner_shape_type& shape_impl() const;
-        const inner_strides_type& strides_impl() const;
-        const inner_backstrides_type& backstrides_impl() const;
+        const inner_shape_type& shape_impl() const noexcept;
+        const inner_strides_type& strides_impl() const noexcept;
+        const inner_backstrides_type& backstrides_impl() const noexcept;
 
-        container_type& data_impl();
-        const container_type& data_impl() const;
+        container_type& data_impl() noexcept;
+        const container_type& data_impl() const noexcept;
 
         friend class xcontainer<pyarray<T>>;
     };
@@ -383,19 +383,19 @@ namespace xt
     }
 
     template <class T>
-    inline auto pyarray<T>::shape_impl() const -> const inner_shape_type&
+    inline auto pyarray<T>::shape_impl() const noexcept -> const inner_shape_type&
     {
         return m_shape;
     }
 
     template <class T>
-    inline auto pyarray<T>::strides_impl() const -> const inner_strides_type&
+    inline auto pyarray<T>::strides_impl() const noexcept -> const inner_strides_type&
     {
         return m_strides;
     }
 
     template <class T>
-    inline auto pyarray<T>::backstrides_impl() const -> const inner_backstrides_type&
+    inline auto pyarray<T>::backstrides_impl() const noexcept -> const inner_backstrides_type&
     {
         // The pyarray object may be copied, invalidating m_backstrides. Building
         // it each time it is needed avoids tricky bugs.
@@ -404,13 +404,13 @@ namespace xt
     }
 
     template <class T>
-    inline auto pyarray<T>::data_impl() -> container_type&
+    inline auto pyarray<T>::data_impl() noexcept -> container_type&
     {
         return m_data;
     }
 
     template <class T>
-    inline auto pyarray<T>::data_impl() const -> const container_type&
+    inline auto pyarray<T>::data_impl() const noexcept -> const container_type&
     {
         return m_data;
     }
diff --git a/include/xtensor-python/pytensor.hpp b/include/xtensor-python/pytensor.hpp
index 27971b9..a3f5383 100644
--- a/include/xtensor-python/pytensor.hpp
+++ b/include/xtensor-python/pytensor.hpp
@@ -140,7 +140,6 @@ namespace xt
 
         void init_tensor(const shape_type& shape, const strides_type& strides);
         void init_from_python();
-        void compute_backstrides();
 
         inner_shape_type& shape_impl() noexcept;
         const inner_shape_type& shape_impl() const noexcept;
@@ -281,7 +280,7 @@ namespace xt
         this->m_ptr = tmp.release().ptr();
         m_shape = shape;
         m_strides = strides;
-        compute_backstrides();
+        adapt_strides(m_shape, m_strides, m_backstrides);
         m_data = container_type(reinterpret_cast<pointer>(PyArray_DATA(this->python_array())),
                                 static_cast<size_type>(PyArray_SIZE(this->python_array())));
     }
@@ -297,20 +296,11 @@ namespace xt
         std::copy(PyArray_DIMS(this->python_array()), PyArray_DIMS(this->python_array()) + N, m_shape.begin());
         std::transform(PyArray_STRIDES(this->python_array()), PyArray_STRIDES(this->python_array()) + N, m_strides.begin(),
                 [](auto v) { return v / sizeof(T); });
-        compute_backstrides();
+        adapt_strides(m_shape, m_strides, m_backstrides);
         m_data = container_type(reinterpret_cast<pointer>(PyArray_DATA(this->python_array())),
                                 static_cast<size_type>(PyArray_SIZE(this->python_array())));
     }
 
-    template <class T, std::size_t N>
-    inline void pytensor<T, N>::compute_backstrides()
-    {
-        for (size_type i = 0; i < m_shape.size(); ++i)
-        {
-            m_backstrides[i] = m_strides[i] * (m_shape[i] - 1);
-        }
-    }
-
     template <class T, std::size_t N>
     inline auto pytensor<T, N>::shape_impl() noexcept -> inner_shape_type&
     {