cleanlab / cleanlab/cleanlab

Improve property-based test for near-duplicate sets

Open
#908 1 comment 2 reactions 0 assignees View on GitHub
good first issue help-wanted
Dominant language
Python
Stars
11.7k
Forks
920
PR merge metrics
No merged PRs in 30d

Description

Property-based tests for near-duplicate sets are randomly failing in CI, when some health-checks don't pass for generated data.
# Stack trace

Every so often, CI randomly fails a test with this error:

```
FAILED tests/datalab/issue_manager/test_duplicate.py::TestNearDuplicateSets::test_near_duplicate_sets_empty_if_no_issue_next - hypothesis.errors.FailedHealthCheck: Examples routinely exceeded the max allowable size. (20 examples overran while generating 8 valid ones). Generating examples this large will usually lead to bad results. You could try setting max_size parameters on your collections and turning max_leaves down on recursive() calls.
See https://hypothesis.readthedocs.io/en/latest/healthchecks.html for more information about this. If you want to disable just this health check, add HealthCheck.data_too_large to the suppress_health_check settings for this test.
```

The way the issue manager is constructed in this test rarely passes the health check. It's failing on unrelated PRs, slowing development down.

A temporary fix was to ignore the health check (suppressing the HealthCheck.data_too_large flag). That's not advisable in the long term, so investigating how to improve the data generation will be a great help!

# Task

Improve the way Hypothesis generates the data for the affected test.

## Update

In https://github.com/cleanlab/cleanlab/pull/902/commits/0f36966ef4246836224afe92a5ab00d91f2d2b5c, the health-check in question has been suppressed. So when working on this issue, remember to remove the `HealthCheck.data_too_large` from `suppress_health_check` and make sure we can scale to more examples without issues.

Contributor guide

Open the contributing guide

Assessment

This issue has not been assessed yet.

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.