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[https://nvbugs/6278377][fix] Prepend a no-quant baseline entry (- accuracy: 88) under… - #15380

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[https://nvbugs/6278377][fix] Prepend a no-quant baseline entry (- accuracy: 88) under…#15380
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tensorrt-cicd:repair-bot-bug6278377

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@tensorrt-cicd tensorrt-cicd commented Jun 15, 2026

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Summary

  • Root cause: references/gsm8k.yaml had only quantized entries (FP8_BLOCK_SCALES, NVFP4) for stepfun-ai/Step-3.7-Flash, so the BF16/auto lookup from test_auto_dtype had no match and raised ValueError("Not registered specs: ...").
  • Fix: Prepend a no-quant baseline entry (- accuracy: 88) under stepfun-ai/Step-3.7-Flash in gsm8k.yaml, matching the existing 88 baseline used for the FP8/NVFP4 variants.
  • Automated fix generated by repair-bot

Test plan

  • Verify fix on the same GPU type as the original failure
  • Check for regressions in related tests

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Summary by CodeRabbit

  • Tests
    • Updated accuracy reference benchmarks for model validation.

….7-Flash GSM8K

The TestStep3_7::test_auto_dtype[tp_size=8-ep_size=8] case loads the
unquantized Step-3.7-Flash checkpoint (no quant_algo, no spec_dec_algo),
but references/gsm8k.yaml only contained quantized entries
(FP8_BLOCK_SCALES, NVFP4) for stepfun-ai/Step-3.7-Flash. The lookup in
AccuracyTask.get_hypothesis_testing_params raised
ValueError("Not registered specs: ...").

Add a no-quant baseline entry (accuracy: 88) so the auto-dtype lookup
matches. Verified on B300 8xGPU: measured 90.26, threshold 84.797.

Signed-off-by: tensorrt-cicd <90828364+tensorrt-cicd@users.noreply.github.com>
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Review Change Stack

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info
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Run ID: 3fa01f2f-f3ba-4b41-97e9-5c4c03a6f070

📥 Commits

Reviewing files that changed from the base of the PR and between 130ae82 and e832f82.

📒 Files selected for processing (1)
  • tests/integration/defs/accuracy/references/gsm8k.yaml

📝 Walkthrough

Walkthrough

A single line is added to the GSM8K accuracy reference YAML file, inserting a new list entry with accuracy: 88 under the stepfun-ai/Step-3.7-Flash model key. No quantization or spec-decoding fields accompany this entry. All existing entries for this model remain unchanged.

Changes

GSM8K Accuracy Reference Update

Layer / File(s) Summary
Add Step-3.7-Flash baseline accuracy entry
tests/integration/defs/accuracy/references/gsm8k.yaml
Adds a new list item with accuracy: 88 for stepfun-ai/Step-3.7-Flash, without quant_algo or spec_dec_algo fields, representing a baseline (unquantized) accuracy reference.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~2 minutes

Suggested reviewers

  • greg-kwasniewski1
  • nvchenghaoz
  • suyoggupta
  • crazydemo
🚥 Pre-merge checks | ✅ 5
✅ Passed checks (5 passed)
Check name Status Explanation
Title check ✅ Passed The title clearly and specifically describes the main change: prepending a no-quant baseline entry with accuracy 88 to gsm8k.yaml for the stepfun-ai/Step-3.7-Flash model, which is the core fix for the test failure.
Description check ✅ Passed The description includes root cause analysis, the specific fix applied, test verification, and bug link, providing clear context for the change. However, it lacks explicit section headers matching the template structure and doesn't include all checklist items.
Docstring Coverage ✅ Passed No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Linked Issues check ✅ Passed Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check ✅ Passed Check skipped because no linked issues were found for this pull request.

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@kaiyux

kaiyux commented Jun 24, 2026

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included the changes in #15583, closing this PR.

@kaiyux kaiyux closed this Jun 24, 2026
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3 participants