Fix MLIR types #650
Merged
Fix MLIR types #650
Conversation
This file contains 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
erick-xanadu
added
reviewer:require-wheels
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #650 +/- ##
=======================================
Coverage 99.41% 99.41%
=======================================
Files 55 55
Lines 9109 9121 +12
Branches 694 701 +7
=======================================
+ Hits 9056 9068 +12
Misses 28 28
Partials 25 25 ☔ View full report in Codecov by Sentry. |
dime10
approved these changes
Apr 9, 2024
|
@erick-xanadu Is it expected that the wheel build fails on this PR? |
|
@dime10 this only fixes one error, which is the MLIR types error, not the macOS dylib error. So, I do expect this to fail the macOS dylib error. |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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Outdated suggestions cannot be applied.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.
Context: There were some errors on CI/CD when testing conversion of numpy types to MLIR types. This is very likely because the context of the expected MLIR types are different from the context of the observed MLIR types.
Description of the Change: Recompute MLIR types each time a conversion from numpy is requested. Do not store them in a dictionary MLIR types in a dictionary.