Comments (4)
originally posted by Joseph Weston (@jbweston) at 2018-07-10T09:40:34.532Z on GitLab
Found a seed where a learner2D test fails (under rescaling) on commit f268c8d:
pytest --randomly-dont-reorganize --randomly-seed=1531149508 adaptive/tests/test_learner.py
@anton-akhmerov points out that because of #83 we should just mark this as xfailing now
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originally posted by Joseph Weston (@jbweston) at 2018-07-10T09:44:42.300Z on GitLab
And another one, also on f268c8d
pytest --randomly-dont-reorganize --randomly-seed=1531215727 adaptive/tests/test_learner.py
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originally posted by Joseph Weston (@jbweston) at 2018-07-10T09:52:18.983Z on GitLab
@basnijholt check this out!
It only fails on some seeds, and the reason that we didn't see it before was probably because the pipelines were always failing and we didn't check/notice which individual tests were failing
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originally posted by Bas Nijholt (@basnijholt) at 2018-09-24T14:26:06.653Z on GitLab
test_expected_loss_improvement_is_less_than_total_loss
for the Learner2D
sometimes fails and sometimes passes. I xfailed it for now in https://gitlab.kwant-project.org/qt/adaptive/commit/eebc5accb225ee570d7419eff57cd351fbd5851c.
pytest --randomly-dont-reorganize --randomly-seed=1537797311
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Related Issues (20)
- make triangulation tests stronger with more randomness HOT 1
- learner tests fail HOT 2
- use a ItemSortedDict for the loss in the LearnerND
- divide by zero warnings in LearnerND
- Issues that can potentially be closed
- Improvements to plotting of the LearnerND
- Learner.load does not raise an exception if the provided filename was not found HOT 5
- Specify an API for defining the scale of point
- (LearnerND) use direct neighbours in loss
- (LearnerND) add advanced usage example HOT 1
- Document and test loss function signatures HOT 4
- Balancing learner does not work with Integrator learner HOT 5
- make triangulation tests stronger with more randomness HOT 1
- learner tests fail HOT 4
- deprecate Learner2D HOT 3
- use a ItemSortedDict for the loss in the LearnerND
- suggested points lie outside of domain HOT 2
- use a ItemSortedDict for the loss in the LearnerND
- Specify an API for defining the scale of point
- Runners should tell learner about remaining points at end of run HOT 1
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