Unit test fail: `test_aurora_small`
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- Python
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Description
I cloned the repo and ran the test suite without modifying any code. One of the unit tests fails:
======================================= short test summary info ========================================
FAILED tests/test_model.py::test_aurora_small - assert (np.float64(0.05390285048894711) / np.float64(276.2245574525479)) <= 0.0001
======================== 1 failed, 55 passed, 38 warnings in 309.24s (0:05:09) =========================
Environment: Python 3.11.11
Dependencies:
numpy==2.3.0
scipy==1.15.3
timm==1.0.15
torch==2.5.1
torchvision==0.20.1
huggingface-hub==0.33.0
OS: MacOS Sonoma 14.4.1
The computed ratio is ~0.000195, slightly above the test threshold of 0.0001. I am not sure if it's a floating‑point precision issue or a logic error.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Begin by reproducing tests/test_model.py::test_aurora_small with the reported environment and inspect the assertion and model path it exercises. Determine whether the discrepancy is numerical or behavioral; done means the test passes for a justified reason and the full suite remains green.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, python, pytorch
- Domain
- machine-learning, testing-qa
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100