[CI] Optimize CI workflow - #7
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apinge merged 2 commits intoJul 31, 2026
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Signed-off-by: Xiake Sun <xiake.sun@amd.com>
Signed-off-by: Xiake Sun <xiake.sun@amd.com>
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Pull request overview
This PR optimizes the Qwen3.5 benchmark GitHub Actions workflow to reduce scheduled job count and improve runner hygiene by consolidating nightly load tests into a single per-model job and tightening per-job cleanup.
Changes:
- Adds a new
load_testbenchmark target that runs pure_text + concurrency + request_rate in one container/server lifecycle. - Introduces ShareGPT dataset path wiring and pre-flight dataset/script validation in CI.
- Updates nightly cron schedule and switches cleanup to only remove the job’s container + image.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 2 comments.
| File | Description |
|---|---|
scripts/ci/sglang_benchmark_workflow.sh |
Adds ShareGPT dataset env wiring, dataset validation helper, and a new load_test mode that runs multiple benchmarks sequentially. |
.github/workflows/sglang_benchmark_workflow.yaml |
Adjusts schedule/dispatch options, collapses nightly benchmark targets to load_test, validates datasets/scripts, reduces benchmark timeout, and limits Docker cleanup to job-owned resources. |
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| import json | ||
| import sys | ||
| from pathlib import Path | ||
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| path = Path(sys.argv[1]) | ||
| if not path.is_file(): | ||
| raise SystemExit(f"ShareGPT dataset not found: {path}") | ||
| try: | ||
| json.loads(path.read_text(encoding="utf-8")) | ||
| except json.JSONDecodeError as exc: | ||
| raise SystemExit(f"ShareGPT dataset is not valid JSON: {path} ({exc})") | ||
| print(f"Using ShareGPT dataset: {path}") |
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| python3 - <<'PY' "${dataset_path}" | ||
| import json | ||
| import sys | ||
| from pathlib import Path | ||
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| path = Path(sys.argv[1]) | ||
| json.loads(path.read_text(encoding="utf-8")) | ||
| print(f"Validated ShareGPT dataset: {path} ({path.stat().st_size} bytes)") | ||
| PY |
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Motivation
Optimizes the Qwen3.5 CI workflow to reduce nightly job count, adjust scheduling, and clean up Docker safely on shared runners.
Modifications
Accuracy Tests
Speed Tests and Profiling
Checklist
Review and Merge Process
/tag-and-rerun-ci,/tag-run-ci-label,/rerun-failed-ci