[GitHub] [arrow] jorisvandenbossche commented on a diff in pull request #33925: GH-33923: [Docs] Tensor canonical extension type specification

["jorisvandenbossche (via GitHub)" <gi...@apache.org>]

jorisvandenbossche commented on code in PR #33925:
URL: https://github.com/apache/arrow/pull/33925#discussion_r1093392443


##########
docs/source/format/CanonicalExtensions.rst:
##########
@@ -72,4 +72,30 @@ same rules as laid out above, and provide backwards compatibility guarantees.
 Official List
 =============
 
-No canonical extension types have been standardized yet.
+Fixed shape tensor
+==================
+
+* Extension name: `arrow.fixed_shape_tensor`.
+
+* The storage type of the extension: ``FixedSizeList`` where:
+
+  * **value_type** is the data type of individual tensors and
+    is an instance of ``pyarrow.DataType`` or ``pyarrow.Field``.
+  * **list_size** is the product of all the elements in tensor shape.
+
+* Extension type parameters:
+
+  * **value_type** = Arrow DataType of the tensor elements
+  * **shape** = shape of the contained tensors as a tuple
+  * **is_row_major** = boolean indicating the order of elements

Review Comment:
   > In torch terminology, making a tensor contiguous (I'm guessing is the same as row major) makes a copy because the underlying memory representation changes.
   
   My understanding is that contiguous tensors in torch are indeed always row-major, but so that also means that if you have such a contiguous tensor, you don't need any copy to put this in the proposed extension TensorArray (or you can get it out without a copy).



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