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Benchmark GitHub Actions workflow (#31163)
* benchmark workflow * benchmark workflow * benchmark workflow * benchmark workflow * build * build * build * build * build * build * build * build * build * build * build * build * build * build --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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.github/workflows/benchmark.yml
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42
.github/workflows/benchmark.yml
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@ -0,0 +1,42 @@
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name: Self-hosted runner (benchmark)
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on:
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schedule:
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- cron: "17 2 * * *"
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workflow_call:
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env:
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HF_HOME: /mnt/cache
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TF_FORCE_GPU_ALLOW_GROWTH: true
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jobs:
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benchmark:
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name: Benchmark
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runs-on: [single-gpu, nvidia-gpu, a10, ci]
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container:
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image: huggingface/transformers-all-latest-gpu
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options: --gpus all --privileged --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
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steps:
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- name: Update clone
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working-directory: /transformers
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run: |
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git fetch && git checkout ${{ github.sha }}
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- name: Reinstall transformers in edit mode (remove the one installed during docker image build)
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working-directory: /transformers
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run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .
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- name: Benchmark (daily)
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if: github.event_name == 'schedule'
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working-directory: /transformers
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run: |
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python3 -m pip install optimum-benchmark>=0.2.0
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HF_TOKEN=${{ secrets.TRANSFORMERS_BENCHMARK_TOKEN }} python3 benchmark/benchmark.py --repo_id hf-internal-testing/benchmark_results --path_in_repo $(date +'%Y-%m-%d') --config-dir benchmark/config --config-name generation --commit=${{ github.sha }} backend.model=google/gemma-2b backend.cache_implementation=null,static backend.torch_compile=false,true --multirun
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- name: Benchmark (merged to main event)
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if: github.event_name == 'push' && github.ref_name == 'main'
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working-directory: /transformers
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run: |
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python3 -m pip install optimum-benchmark>=0.2.0
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HF_TOKEN=${{ secrets.TRANSFORMERS_BENCHMARK_TOKEN }} python3 benchmark/benchmark.py --repo_id hf-internal-testing/benchmark_results_merge_event --path_in_repo $(date +'%Y-%m-%d') --config-dir benchmark/config --config-name generation --commit=${{ github.sha }} backend.model=google/gemma-2b backend.cache_implementation=null,static backend.torch_compile=false,true --multirun
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.github/workflows/push-important-models.yml
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5
.github/workflows/push-important-models.yml
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@ -133,3 +133,8 @@ jobs:
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slackChannel: ${{ secrets.SLACK_CIFEEDBACK_CHANNEL }}
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slackToken: ${{ secrets.SLACK_CIFEEDBACK_BOT_TOKEN }}
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waitForSSH: true
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benchmark:
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name: Benchmark workflow
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uses: ./.github/workflows/benchmark.yml
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secrets: inherit
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@ -32,6 +32,8 @@ from pathlib import Path
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from git import Repo
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from huggingface_hub import HfApi
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from optimum_benchmark import Benchmark
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from optimum_benchmark_wrapper import main
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@ -143,7 +145,6 @@ def summarize(run_dir, metrics, expand_metrics=False):
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with open(os.path.join(report_dir, "summary.json"), "w") as fp:
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json.dump(summary, fp, indent=4)
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# TODO: upload to Hub
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return summaries
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@ -191,7 +192,6 @@ def combine_summaries(summaries):
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with open(os.path.join(exp_run_dir, "summary.json"), "w") as fp:
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json.dump(combined, fp, indent=4)
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# TODO: upload to Hub
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print(json.dumps(combined, indent=4))
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return combined
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@ -216,6 +216,11 @@ if __name__ == "__main__":
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help="Comma-separated list of branch names and/or commit sha values on which the benchmark will run. If `diff` is specified, it will run on both the current head and the `main` branch.",
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)
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parser.add_argument("--metrics", type=str, help="The metrics to be included in the summary.")
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parser.add_argument("--repo_id", type=str, default=None, help="The repository to which the file will be uploaded.")
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parser.add_argument("--path_in_repo", type=str, default=None, help="Relative filepath in the repo.")
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parser.add_argument("--token", type=str, default=None, help="A valid user access token (string).")
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args, optimum_benchmark_args = parser.parse_known_args()
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repo = Repo(PATH_TO_REPO)
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@ -308,3 +313,14 @@ if __name__ == "__main__":
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json.dump(run_summaries, fp, indent=4)
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combined_summary = combine_summaries(run_summaries)
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if args.repo_id is not None and args.path_in_repo is not None:
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# Upload to Hub
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api = HfApi()
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api.upload_folder(
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folder_path=exp_run_dir,
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path_in_repo=args.path_in_repo,
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repo_id=args.repo_id,
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repo_type="dataset",
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token=args.token,
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)
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