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refactor: make benchmark runtime native - #65

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refactor/integrate-replication-protocols
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melvinbarbaux wants to merge 2 commits into
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refactor/integrate-replication-protocols

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Summary

What does this PR change?

Checklist

  • Tests added or updated
  • CI green
  • Changelog updated
  • Documentation updated

Notes

Anything reviewers should know?

Comment thread tests/bench/test_pipeline_capabilities.py Fixed
Comment thread tests/runtime/test_contracts.py Fixed
Comment thread src/modssc/inductive/methods/co_training.py Fixed
@melvinbarbaux
melvinbarbaux force-pushed the refactor/integrate-replication-protocols branch from de1fb52 to f24ff0d Compare August 29, 2026 23:32
Comment thread tests/data_loader/test_cache.py Fixed
Comment thread tests/runtime/test_continuation.py Fixed
Comment thread tests/runtime/test_continuation.py Fixed
@melvinbarbaux
melvinbarbaux force-pushed the refactor/integrate-replication-protocols branch from f24ff0d to e0c5048 Compare August 29, 2026 23:50
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codecov Bot commented Aug 29, 2026

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Codecov Report

✅ All modified and coverable lines are covered by tests.

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@melvinbarbaux
melvinbarbaux force-pushed the refactor/integrate-replication-protocols branch 4 times, most recently from 96f714f to cdd288c Compare August 31, 2026 02:03
lock.write_bytes(b"")
os.link(lock, tmp_path / "copy")
with pytest.raises(ManifestError, match="single-link regular file"):
cache._open_lock_file(lock)
@melvinbarbaux
melvinbarbaux force-pushed the refactor/integrate-replication-protocols branch 6 times, most recently from 3847b9f to 84e3969 Compare September 1, 2026 16:24
@melvinbarbaux
melvinbarbaux force-pushed the refactor/integrate-replication-protocols branch from 84e3969 to 77dae2a Compare September 2, 2026 14:04
- Introduced tests for the WEKA J48 classifier, validating its integration with the specified Weka version and ensuring proper handling of training and prediction scenarios.
- Added tests for the GRAND method in GNN, including checks for sparse matrix operations and propagation consistency.
- Implemented convergence diagnostics for Poisson learning methods, ensuring accurate reporting of iteration caps and residual norms.
- Enhanced the selection evaluator for transductive methods, ensuring proper handling of training, validation, and test splits.
- Added regression tests to verify that the unlabeled pool includes all hidden nodes without exposing evaluation labels.
generation = record["generation"]
if isinstance(generation, str):
return step_root / _GENERATIONS_DIRNAME / generation
except (KeyError, PreprocessCacheError, TypeError):

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