b8fc24e092
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| .. | ||
| README.md | ||
| __init__.py | ||
| check_disabled_tests.py | ||
| export_test_times.py | ||
| import_test_stats.py | ||
| monitor.py | ||
| upload_artifacts.py | ||
| upload_dynamo_perf_stats.py | ||
| upload_external_contrib_stats.py | ||
| upload_metrics.py | ||
| upload_sccache_stats.py | ||
| upload_stats_lib.py | ||
| upload_test_stat_aggregates.py | ||
| upload_test_stats.py | ||
README.md
PyTorch CI Stats
We track various stats about each CI job.
- Jobs upload their artifacts to an intermediate data store (either GitHub
Actions artifacts or S3, depending on what permissions the job has). Example:
a9f6a35a33/.github/workflows/_linux-build.yml (L144-L151) - When a workflow completes, a
workflow_runevent triggersupload-test-stats.yml. upload-test-statsdownloads the raw stats from the intermediate data store and uploads them as JSON to Rockset, our metrics backend.
graph LR
J1[Job with AWS creds<br>e.g. linux, win] --raw stats--> S3[(AWS S3)]
J2[Job w/o AWS creds<br>e.g. mac] --raw stats--> GHA[(GH artifacts)]
S3 --> uts[upload-test-stats.yml]
GHA --> uts
uts --json--> R[(Rockset)]
Why this weird indirection? Because writing to Rockset requires special permissions which, for security reasons, we do not want to give to pull request CI. Instead, we implemented GitHub's recommended pattern for cases like this.
For more details about what stats we export, check out
upload-test-stats.yml