Fix MindtPy bugs #3034
Fix MindtPy bugs #3034
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This is waiting for #2988 to be merged first |
Codecov ReportAttention:
Additional details and impacted files@@ Coverage Diff @@
## main #3034 +/- ##
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+ Coverage 88.29% 88.32% +0.03%
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Files 832 832
Lines 92234 92253 +19
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+ Hits 81438 81484 +46
+ Misses 10796 10769 -27
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The |
| @@ -1 +1 @@ | |||
| __version__ = (0, 1, 0) | |||
| __version__ = (1, 0, 0) | |||
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Should your changelog in line 54 of Mindtpy.py match this version number?
| except KeyError as e: | ||
| self.config.logger.error(str(e) + '\nDeactivating no-good cuts failed.') | ||
| self.config.logger.error(e, exc_info=True) | ||
| self.config.logger.error('Deactivating no-good cuts failed.') |
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How can this fail? Wouldn't this be a DeveloperError (if you need an error here at all) since mindtpy can keep track of what cuts it has added?
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Thanks for pointing this out. I checked the log of the benchmark tests and found this error came out when timelimit was reached. Let me try to fix it before merging this PR. Thanks.
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The KeyError happens when no feasible solution has been found within the timelimit. I added one more condition for the fix_dual_bound function in the OA, GOA, LP/NLP B&B and GLP/NLP B&B methods.
I also removed fix_dual_bound for the ECP method since we will never add no-good cuts in the ECP method.
I would appreciate it if @bernalde can give it a double-check.
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Ah, okay. I think a different error message might be clearer then--it's not deactivating the cuts that failed, it's the solve after you deactivated them (if I'm understanding correctly).
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I have already run the black format locally. Are there any new requirements for the black format? |
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@ZedongPeng - check your black version. They released an update this month that made some changes. |
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@ZedongPeng I have a couple minor edits but otherwise I think this looks good.
Co-authored-by: Bethany Nicholson <blnicho@users.noreply.github.com>
Co-authored-by: Bethany Nicholson <blnicho@users.noreply.github.com>
Fixes # .
Summary/Motivation:
This PR fixes several bugs in MindtPy according to the benchmark results.
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