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Fix comment on broadcasting example to clarify dimension mismatch (#162177)

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Fixes #162116

Updated the comment in the broadcasting example to clarify that tensors with mismatched dimension sizes (0 vs 2) are not broadcastable. Removed incorrect reference to missing dimensions.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/162177
Approved by: https://github.com/soulitzer
This commit is contained in:
Dev Sashidhar
2025-09-29 16:47:45 +00:00
committed by PyTorch MergeBot
parent 84b57c93db
commit 5ff2387dbe
1 changed files with 2 additions and 2 deletions
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docs/source/notes/broadcasting.rst
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@ -13,7 +13,6 @@ General semantics
-----------------
Two tensors are "broadcastable" if the following rules hold:
- Each tensor has at least one dimension.
- When iterating over the dimension sizes, starting at the trailing dimension,
the dimension sizes must either be equal, one of them is 1, or one of them
does not exist.
@ -26,7 +25,8 @@ For Example::
>>> x=torch.empty((0,))
>>> y=torch.empty(2,2)
# x and y are not broadcastable, because x does not have at least 1 dimension
# x and y are not broadcastable, because the 0-sized dimension of x
# does not match the 2-sized dimension of y.
# can line up trailing dimensions
>>> x=torch.empty(5,3,4,1)