thomasw21 commented on code in PR #33925:
URL: https://github.com/apache/arrow/pull/33925#discussion_r1095646988
##########
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:
I don't know if that helps the discussion:
```python
import torch
def get_1d_memory_buffer(tensor):
return "".join(hex(elt) for elt in x.storage().untyped().byte())
x = torch.randn(2,3)
y = torch.empty(3,2).transpose(0,1)
# Fill y with x data
y[:] = x
assert x.shape == y.shape
assert get_1d_memory_buffer(x) != get_1d_memory_buffer(y)
# You can try printing `x` and `y` and you'll see that the tensors are the
same
```
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