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Quote nn.Module annotations so torch stays optional - #97
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #97 +/- ##
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+ Coverage 96.09% 96.16% +0.07%
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dilpath
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Should we rather just reintroduce from __future__ import annotations -- what was the reason for removing that? Both fine for me
9b60487 removed `from __future__ import annotations` from nn_model.py, so the nn.Module annotations are evaluated at import time. Without torch installed, `nn` is undefined and importing petab_sciml (and therefore petab.v2) fails with NameError. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Given that you don't know the reason for removing |
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petab_sciml 9d076fe dropped `from __future__ import annotations` from nn_model.py, so importing petab.v2 failed with NameError wherever torch was not installed. Pin to 76a2006 (PEtab-dev/petab_sciml#97), which restores it, and bring the docs requirements in line. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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9b60487 removed
from __future__ import annotationsfrom nn_model.py, so the nn.Module annotations are evaluated at import time. Without torch installed,nnis undefined and importing petab_sciml (and therefore petab.v2) fails with NameError. Restore the future import.This is in service of bumping the petab-sciml pin in AMICI, so we can avoid installing torch in more workflows: AMICI-dev/AMICI#3502