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Populate inform dict for all optimizers #394

Merged
merged 6 commits into from
Apr 24, 2024
Merged

Populate inform dict for all optimizers #394

merged 6 commits into from
Apr 24, 2024

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ewu63
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@ewu63 ewu63 commented Apr 23, 2024

Purpose

Closes #393.

Expected time until merged

1 day.

Type of change

  • Bugfix (non-breaking change which fixes an issue)
  • New feature (non-breaking change which adds functionality)
  • Breaking change (non-backwards-compatible fix or feature)
  • Code style update (formatting, renaming)
  • Refactoring (no functional changes, no API changes)
  • Documentation update
  • Maintenance update
  • Other (please describe)

Testing

Checklist

  • I have run flake8 and black to make sure the Python code adheres to PEP-8 and is consistently formatted
  • I have formatted the Fortran code with fprettify or C/C++ code with clang-format as applicable
  • I have run unit and regression tests which pass locally with my changes
  • I have added new tests that prove my fix is effective or that my feature works
  • I have added necessary documentation

@ewu63 ewu63 requested a review from a team as a code owner April 23, 2024 22:37
@ewu63 ewu63 requested review from marcomangano and ArshSaja April 23, 2024 22:37
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codecov bot commented Apr 23, 2024

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 74.07%. Comparing base (69c2a6f) to head (cec9046).

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #394      +/-   ##
==========================================
+ Coverage   73.72%   74.07%   +0.34%     
==========================================
  Files          22       22              
  Lines        3292     3290       -2     
==========================================
+ Hits         2427     2437      +10     
+ Misses        865      853      -12     

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@marcomangano
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marcomangano commented Apr 23, 2024

The flake8 error is fixed in #392, we need to merge that PR before this one

@ewu63
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ewu63 commented Apr 23, 2024

@marcomangano I would prefer if we do a patch bump asap rather than waiting for #388 (which I expect will take a bit of time?)

As an aside, I do miss my sudo powers...

@marcomangano
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@marcomangano I would prefer if we do a patch bump asap rather than waiting for #388 (which I expect will take a bit of time?)

#388 is ready to go once this is merged

@sseraj sseraj merged commit 01d5111 into main Apr 24, 2024
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@sseraj sseraj deleted the bugfix/nsga2 branch April 24, 2024 18:12
sol_inform = {}
# sol_inform['value'] = inform
# sol_inform['text'] = self.informs[inform[0]]
sol_inform = {"value": "", "text": ""}
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@swryan swryan Apr 29, 2024

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Was "value" intentionally set to a string value in these optimizers?

As far as I can tell, this was always meant to be an integer return code, and we have logic that expects that to be the case:

File "/home/swryan/dev/OpenMDAO/openmdao/drivers/pyoptsparse_driver.py", line 680, in run
    if exit_status > 2:
       ^^^^^^^^^^^^^^^
TypeError: '>' not supported between instances of 'str' and 'int'

Just wondering what the circumstances would be where we should expect this value to be a string...

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@swryan swryan Apr 29, 2024

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Hmmm.. I see that we were checking if "value" was in the dict.. and if it is there we expect it to be an int....

So we were handling the case for the optimizers that didn't populate it... I guess we should consider an empty string value to be an indication that the optimizer doesn't provide the value...

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Yeah I see, I guess we need to agree on a convention for optimizers that don't have any informs. I'm happy to do whatever you guys want, which could be

  • None
  • empty string (current)
  • some default inform that just says optimization completed

In the longer term, we should probably make dataclasses and type annotate these better.

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In retrospect this PR is probably not the best implementation, and was done purely to make the solution object printing work without changing the logic there...

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@swryan swryan Apr 29, 2024

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yeah, it may be that just updating pyOpt_solution.py to only print values for those keys if they exist might a preferable solution, keeping the semantics/typing a bit more rigorous, but it's easy enough for us to handle the empty string (which we will do). Also agree with your long term thoughts.

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print (sol) of nsga2 is error
4 participants