[test] Add accuracy regression test for Mistral3.1 #6322
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WalkthroughA new model, Changes
Sequence Diagram(s)sequenceDiagram
participant Tester as TestMistralSmall24B
participant LLM as LLM Model
participant Tasks as Evaluation Tasks
Tester->>LLM: Instantiate with MODEL_PATH
loop For each task (CnnDailymail, MMLU, GSM8K)
Tester->>Tasks: Evaluate task with MODEL_NAME
Tasks->>LLM: Query model for predictions
LLM-->>Tasks: Return results
Tasks-->>Tester: Return evaluation metrics
end
Estimated code review effort🎯 2 (Simple) | ⏱️ ~8 minutes Suggested reviewers
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Signed-off-by: William Zhang <[email protected]>
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Actionable comments posted: 1
🧹 Nitpick comments (2)
tests/integration/defs/accuracy/references/cnn_dailymail.yaml (1)
191-192: Minor ordering nit – keep new models sorted for quicker diffing.Files aren’t strictly alphabetised, but adding new keys in sorted order helps future merges and reduces rebase noise.
Consider moving this block to maintain the existing (roughly) alphabetical grouping within the mistralai section.tests/integration/defs/accuracy/references/mmlu.yaml (1)
98-99: Value & structure OK – double-check decimal precision.Two-decimal precision (
81.7) is fine, but neighbouring entries mostly keep two decimals after the point (e.g.71.35). If you want full consistency, record this as81.70.
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📒 Files selected for processing (5)
tests/integration/defs/accuracy/references/cnn_dailymail.yaml(1 hunks)tests/integration/defs/accuracy/references/gsm8k.yaml(1 hunks)tests/integration/defs/accuracy/references/mmlu.yaml(1 hunks)tests/integration/defs/accuracy/test_llm_api_pytorch.py(1 hunks)tests/integration/test_lists/test-db/l0_h100.yml(1 hunks)
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🔇 Additional comments (2)
tests/integration/defs/accuracy/references/gsm8k.yaml (1)
123-124: Entry looks good – confirm consistency across datasets.
mistralai/Mistral-Small-3.1-24B-Instruct-2503is added with a single accuracy record; format and indentation match neighbouring entries.
Just make sure the same model string is spelled identically in all three reference YAMLs and in the new test class to avoid lookup/key-mismatch at runtime.tests/integration/defs/accuracy/test_llm_api_pytorch.py (1)
493-505: LGTM! Well-structured accuracy regression test implementation.The new
TestMistralSmall24Bclass follows the established patterns in the codebase perfectly:
- Proper inheritance from
LlmapiAccuracyTestHarness- Consistent naming convention for
MODEL_NAMEandMODEL_PATH- Standard test method that evaluates the model against three common accuracy benchmarks (CnnDailymail, MMLU, GSM8K)
The implementation aligns with the PR objective of adding an accuracy regression test for Mistral3.1 and maintains consistency with existing test classes in the file.
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Signed-off-by: William Zhang <[email protected]> Signed-off-by: Lanyu Liao <[email protected]>
4 participants
Summary by CodeRabbit
[TRTLLM-6598] [test] Add accuracy regression test for Mistral3.1
Description
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