[ROCm][CI] Fix Assertion Logic For test_gpt_oss#35806
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DarkLight1337 merged 1 commit intovllm-project:mainfrom Mar 3, 2026
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[ROCm][CI] Fix Assertion Logic For test_gpt_oss#35806DarkLight1337 merged 1 commit intovllm-project:mainfrom
test_gpt_oss#35806DarkLight1337 merged 1 commit intovllm-project:mainfrom
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Signed-off-by: Micah Williamson <micah.williamson@amd.com>
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This pull request addresses a flaky test, test_gpt_oss, which was failing in the AMD CI. The original assertion incorrectly rejected valid accuracy scores that were higher than the expected value plus a tolerance. The fix correctly adjusts the assertion to check only if the measured accuracy meets a minimum threshold (expected_accuracy - rtol), which is the standard practice for such tests. Additionally, an unused general importlib import was replaced with the more specific importlib.util. The changes are correct and well-implemented.
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LGTM, thanks!
The original threshold might be a bit tight on the upper end.
DarkLight1337
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After #35658 was merged, we saw
Quantized Models Teststarted failing in AMD CI:https://buildkite.com/vllm/amd-ci/builds/5661/steps/canvas?sid=019cad58-e61d-4bf9-8028-1a6a6a7ac897&tab=output
As it turns out, this test was previously skipped because quark was not installed in our CI builds. Now that it is, it exposed that this test was flaky because it doesn't allow for measured accuracy that is higher than the expected accuracy. Before this PR, tests sometimes fail with errors like
AssertionError: Expected: 0.89 | Measured: 0.913151364764268. (e.g. you can observe this withpytest -v -s models/quantization/test_gpt_oss.py::test_gpt_oss_attention_quantization[amd/gpt-oss-20b-WFP8-AFP8-KVFP8-0.89-1]). Clearly, 0.91 is a perfectly valid accuracy score, so we should accept it.