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Signed-off-by: Helen Zhao <shanjiaz@ip-172-31-44-201.us-west-2.compute.internal>
📝 WalkthroughWalkthrough
ChangesGuidellm dataset loading
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🧹 Nitpick comments (1)
scripts/evaluate/perf_utils.py (1)
568-568: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winAdd a regression assertion for the explicit split.
tests/unit/scripts/test_perf_utils.pycurrently verifiesload_kwargs.data_files=qa.jsonlbut notload_kwargs.split=train, so the reported regression could return without failing the test.Suggested test assertion
assert "load_kwargs.data_files=qa.jsonl" in data +assert "load_kwargs.split=train" in data🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@scripts/evaluate/perf_utils.py` at line 568, Update the relevant test in tests/unit/scripts/test_perf_utils.py to assert that the generated configuration includes load_kwargs.split=train, alongside the existing data_files=qa.jsonl assertion. Use the test covering the perf utility output affected by the load_kwargs construction.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Nitpick comments:
In `@scripts/evaluate/perf_utils.py`:
- Line 568: Update the relevant test in tests/unit/scripts/test_perf_utils.py to
assert that the generated configuration includes load_kwargs.split=train,
alongside the existing data_files=qa.jsonl assertion. Use the test covering the
perf utility output affected by the load_kwargs construction.
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📒 Files selected for processing (1)
scripts/evaluate/perf_utils.py
Purpose
Fix guidellm HuggingFace data loading by adding explicit split=train to load_kwargs. Without this, guidellm 0.7.x receives a DatasetDict instead of a Dataset, causing benchmark runs to fail.
Tests
Run python evaluate.py throughput --target /v1 --subsets HumanEval against a live vLLM server to verify the fix
Checklist
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