Update DLPack content to address unsupported use cases

spec/draft/design_topics/data_interchange.rst

@@ -84,3 +84,19 @@ page gives a high-level specification for data exchange in Python using DLPack.
    are recommended to do so using the same syntax and semantics as outlined
    below. They are not required to return an array object from ``from_dlpack``
    which conforms to this standard.
+
+Non-supported use cases
+-----------------------
+
+Use of DLPack requires that the data can be represented by a strided, in-memory
+layout on a single device. This covers usage by a large range of, but not all,
+known and possible array libraries. Use cases that are not supported by DLPack
+include:
+
+- Distributed arrays, i.e., the data residing on multiple nodes or devices,
+- Sparse arrays, i.e., sparse representations where a data value (typically
+  zero) is implicit.
+
+There may be other reasons why it is not possible or desirable for an
+implementation to materialize the array as strided data in memory. In such
+cases, the implementation may raise a `BufferError` in the `__dlpack__` method.

src/array_api_stubs/_draft/creation_functions.py

@@ -232,6 +232,15 @@ def from_dlpack(x: object, /) -> array:
            :class: note
 
            The returned array may be either a copy or a view. See :ref:`data-interchange` for details.
+
+    Raises
+    ------
+    BufferError
+        The ``__dlpack__`` method on the input array may raise ``BufferError``
+        when the data cannot be exported as DLPack (e.g., incompatible dtype or
+        strides). It may also raise other errors when export fails for other
+        reasons (e.g., not enough memory available to materialize the data).
+        ``from_dlpack`` must propagate such exceptions.
     """