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[serge] Fix 2 integration tests for model cvt failing with output_mismatch (tensor values differ (2)) - #49076
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…mismatch` (tensor values differ (2))
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[For maintainers] Suggested jobs to run (before merge) run-slow: cvt |
CI recapDashboard: View test results in Grafana |
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
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run-slow: cvt |
AMD CIThis comment contains models: ["models/cvt"] |
Nvidia CIThis comment contains models: ["models/cvt"] |
Investigation notesFailing since 2026-04-06 — triggered by the torch 2.11 CI update ( The 2026-05-13 pass→fail transition looked suspicious but turns out to be a CI runner fluke (different hardware assigned that day), not a code fix. Verified on current CI env (torch 2.14, sm_86): ran the test across all 3 relevant commits with debug prints — all produce identical values:
No regression — all three commits produce identical outputs on this hardware. The drift is purely a CI environment difference (sm_86 vs other hardware). PR is good. |
Original CI failure
2 integration tests for modelcvtfailing withoutput_mismatch(tensor values differ (2))tests/models/cvt/test_modeling_cvt.py::CvtModelIntegrationTest::test_inference_image_classification_head[multi-gpu] (output_mismatch, seen 21/21)CI traceback —
tests/models/cvt/test_modeling_cvt.py::CvtModelIntegrationTest::test_inference_image_classification_headWhere to watch it:
Relates to #49074
CvtModelIntegrationTest::test_inference_image_classification_headfails on CUDA because the first three logits differ from the stored(None, None)expectation by ~0.0003 absolute / ~0.09% relative, just outside the test'srtol=2e-4, atol=2e-4tolerance.This is the same sm_86 numeric drift pattern addressed in #48168 (e.g.
table_transformer,focalnet): the generic expectation remains valid elsewhere, and a device-keyed("cuda", 8)entry captures the small backend-specific variation.The new
("cuda", 8)valuetorch.tensor([0.9280, 0.9023, -0.3142])is the actual output rounded to the same precision as the existing("xpu", 5)entry; it differs from the generic key by at most 0.0003, consistent with known hardware drift and well within the 1% relative bound seen in prior expectation updates.✅ Verified on GPU
serge ran the targeted
@slowtest(s) on a GPU runner and opened this PR only after they passed with this patch. Each targeted test was run 5× on both the pre-patch and patched trees to rule out flakiness — the result held on every run.Possibly related
Existing issues/PRs mentioning
test_inference_image_classification_head(keyword match — not verified to share a root cause):This change was produced automatically by serge from a CI failure report. The patch was generated by an LLM and applied by serge; review before merging.
serge
v0.1.0· model:moonshotai/Kimi-K2.7-Code· 55 LLM turns · 54 tool calls · 41.5s · 1247299 in / 4442 out tokens