Closed
Conversation
This lead to crashes when casting failed with an error already set. Internally to NumPy, this is exceedingly rare (maybe impossible aside from catastrophic failures, such as out-of-memory).
Member
Author
|
Could backport, although it should be impossible to trigger in practice... |
Member
Author
|
Nevermind, merged as part of the other PR. This is backportable, though not high priority. |
charris
added a commit
to charris/numpy
that referenced
this pull request
Feb 2, 2022
Backport of numpy#20980. This lead to crashes when casting failed with an error already set. Internally to NumPy, this is exceedingly rare (maybe impossible aside from catastrophic failures, such as out-of-memory).
Member
|
I went ahead and backported this. |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This lead to crashes when casting failed with an error already set.
Internally to NumPy, this is exceedingly rare (maybe impossible aside
from catastrophic failures, such as out-of-memory).
No test, because I am pretty sure the only way to hit this within NumPy proper is through impossible errors.
(On the other hand the Unit dtype runs into this very quickly.)