📜 Add documentation and diagrams on the plugin architecture #2132
Workflow file for this run
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| name: Test | |
| on: | |
| # Don't use `paths` or `paths-ignore` filter since this workflow is required | |
| # for all pull requests on main irrespective of file type or location | |
| # Use `changed-src-files` step to determine if source code was changed | |
| pull_request: | |
| # add labeled and unlabeled to the default types (runs when label is added) | |
| types: [opened, synchronize, reopened, labeled, unlabeled, auto_merge_enabled] | |
| branches: [main] | |
| push: | |
| branches: [main] | |
| workflow_dispatch: | |
| env: | |
| FORCE_COLOR: "1" | |
| VLLM_CPU_DISABLE_AVX512: "true" | |
| VLLM_TARGET_DEVICE: "empty" | |
| VLLM_PLUGINS: "spyre" | |
| HF_HUB_CACHE: "${{ github.workspace }}/.cache/huggingface/hub" | |
| DEFAULT_HF_MODEL: "ibm-ai-platform/micro-g3.3-8b-instruct-1b" | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }} | |
| cancel-in-progress: true | |
| jobs: | |
| test: | |
| timeout-minutes: 20 | |
| runs-on: ${{ matrix.os }} | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| os: ["ubuntu-latest"] | |
| python_version: ["3.12"] | |
| vllm_version: | |
| - name: "default" | |
| repo: "" | |
| - name: "vLLM:main" | |
| repo: "git+https://github.com/vllm-project/vllm --branch main" | |
| test_suite: | |
| - name: "static batching" | |
| markers: "cpu and decoder and not cb and not other_e2e and not quantized" | |
| flags: "--timeout=300" | |
| hf_models: "JackFram/llama-160m" | |
| - name: "fp8" | |
| markers: "cpu and quantized and multi" | |
| flags: "--timeout=600 -k 'basic and test_output' --durations=0" | |
| hf_models: "ibm-ai-platform/micro-g3.3-8b-instruct-1b-FP8" | |
| - name: "embedding" | |
| markers: "cpu and embedding and not quantized" | |
| flags: "--timeout=300" | |
| hf_models: "sentence-transformers/all-roberta-large-v1" | |
| - name: "scoring" | |
| markers: "cpu and scoring" | |
| flags: "--timeout=300" | |
| hf_models: "cross-encoder/stsb-roberta-large" | |
| - name: "continuous batching" | |
| markers: "cpu and cb and not quantized" | |
| flags: "--timeout=300 --durations=0 -s" | |
| - name: "worker and utils" | |
| markers: "not e2e and not quantized" | |
| flags: "--timeout=300" | |
| - name: "compatibility" | |
| markers: "compat" | |
| flags: "--timeout=300" | |
| - name: "other e2e" | |
| markers: "cpu and other_e2e and not quantized" | |
| flags: "--timeout=300" | |
| - name: "precompilation" | |
| markers: "precompilation and not quantized" | |
| flags: "--timeout=300" | |
| include: | |
| - vllm_version: | |
| name: "vLLM:lowest" | |
| repo: "git+https://github.com/vllm-project/vllm --tag v0.10.2" | |
| test_suite: | |
| name: "backward compat" | |
| markers: "compat or (cpu and basic)" | |
| flags: "--timeout=300" | |
| hf_models: "micro-g3.3_roberta-large" | |
| os: "ubuntu-latest" | |
| python_version: "3.12" | |
| # Exclude vLLM:main if PR does NOT have "ready" label AND auto-merge is not enabled | |
| exclude: >- | |
| ${{ | |
| github.event_name == 'pull_request' && | |
| !( | |
| contains(toJson(github.event.pull_request.labels), '"ready"') || | |
| github.event.action == 'auto_merge_enabled' | |
| ) | |
| && fromJSON('[{"vllm_version":{"name":"vLLM:main"}}]') | |
| || fromJSON('[]') | |
| }} | |
| name: "${{ matrix.test_suite.name }} (${{ matrix.vllm_version.name }})" | |
| steps: | |
| - name: "Checkout" | |
| uses: actions/checkout@v4 | |
| with: | |
| fetch-depth: 1 | |
| - name: "Get changed source files" | |
| id: changed-src-files | |
| uses: tj-actions/changed-files@v46 | |
| with: # Avoid using single or double quotes for multiline patterns | |
| files: | | |
| .github/workflows/test.yml | |
| pyproject.toml | |
| uv.lock | |
| tests/**/*.py | |
| vllm_spyre/**/*.py | |
| - name: "Install PyTorch 2.7.1" | |
| if: steps.changed-src-files.outputs.any_changed == 'true' | |
| run: | | |
| pip install torch=="2.7.1+cpu" --index-url https://download.pytorch.org/whl/cpu | |
| - name: "Install uv" | |
| if: steps.changed-src-files.outputs.any_changed == 'true' | |
| uses: astral-sh/setup-uv@v5 | |
| with: | |
| version: "latest" | |
| python-version: ${{ matrix.python_version }} | |
| enable-cache: true | |
| ignore-nothing-to-cache: true | |
| cache-dependency-glob: | | |
| pyproject.toml | |
| - name: "Set vLLM version" | |
| if: ( steps.changed-src-files.outputs.any_changed == 'true' && matrix.vllm_version.repo ) | |
| run: | | |
| uv add ${{ matrix.vllm_version.repo }} | |
| echo "TEST_VLLM_VERSION=${{ matrix.vllm_version.name }}" >> "$GITHUB_ENV" | |
| - name: "Install vLLM with Spyre plugin" | |
| if: steps.changed-src-files.outputs.any_changed == 'true' | |
| run: | | |
| uv venv .venv --system-site-packages | |
| source .venv/bin/activate | |
| # Syncs both the runtime and dev deps, based on the lockfile contents | |
| uv sync --frozen | |
| # Builds and installs the vllm_spyre wheel into .venv | |
| # This needs to be done after `uv sync`, or the wheel install will be | |
| # overwritten. | |
| uv pip install -v . | |
| # Standardize model name for cache keys | |
| - name: Standardize HF model name | |
| id: standardize-names | |
| run: | | |
| model="${{ matrix.test_suite.hf_models || env.DEFAULT_HF_MODEL }}" | |
| if [[ "$model" == "micro-g3.3_roberta-large" ]]; then | |
| echo "model_key=micro-g3.3_roberta-large" >> "$GITHUB_ENV" | |
| echo "model_path=${HF_HUB_CACHE}" >> "$GITHUB_ENV" | |
| else | |
| # replace / with -- | |
| safe_name="${model//\//--}" | |
| echo "model_key=$safe_name" >> "$GITHUB_ENV" | |
| echo "model_path=${HF_HUB_CACHE}/models--$safe_name" >> "$GITHUB_ENV" | |
| fi | |
| - name: "Restore HF models cache" | |
| id: cache_restore | |
| if: steps.changed-src-files.outputs.any_changed == 'true' | |
| uses: actions/cache/restore@v4 | |
| with: | |
| path: ${{ env.model_path }} | |
| key: ${{ runner.os }}-hf-model-${{ env.model_key }} | |
| - name: "Download HF models" | |
| if: ( steps.changed-src-files.outputs.any_changed == 'true' && steps.cache_restore.outputs.cache-hit != 'true' ) | |
| run: | | |
| # We are caching HF models (HF_HUB_CACHE) for reliability rather than speed, since HF downloads are flaky for concurrent jobs. | |
| # Be careful when adding models to the cache here, as the GHA cache is limited to 10 GB. | |
| # If a new model is added here, a new hash key is generated. The previous cache blob can then | |
| # be removed by an admin or can be left to expire after 7 days. | |
| download_tinygranite() { | |
| python -c "from transformers import pipeline, AutoTokenizer; pipeline('text-generation', model='$1'); tokenizer=AutoTokenizer.from_pretrained('$1')" | |
| } | |
| download_roberta_large() { | |
| python -c "from sentence_transformers import SentenceTransformer; SentenceTransformer('$1')" | |
| } | |
| # tinyllama used for static batching tests because static batching is _too slow_ | |
| download_tinyllama() { | |
| python -c "from transformers import pipeline; pipeline('text-generation', model='$1')" | |
| } | |
| hf_models="${{ matrix.test_suite.hf_models || env.DEFAULT_HF_MODEL }}" | |
| if [[ "$hf_models" == "micro-g3.3_roberta-large" ]]; then | |
| models=("ibm-ai-platform/micro-g3.3-8b-instruct-1b" "sentence-transformers/all-roberta-large-v1") | |
| else | |
| models=("$hf_models") | |
| fi | |
| for model in "${models[@]}"; do | |
| echo "Downloading $model ..." | |
| case "$model" in | |
| "ibm-ai-platform/micro-g3.3-8b-instruct-1b"*) | |
| download_tinygranite "$model" & | |
| ;; | |
| "JackFram/llama-160m") | |
| download_tinyllama "$model" & | |
| ;; | |
| "sentence-transformers/all-roberta-large-v1") | |
| download_roberta_large "$model" & | |
| ;; | |
| "cross-encoder/stsb-roberta-large") | |
| download_roberta_large "$model" & | |
| ;; | |
| *) | |
| echo "No download method found for: $model"; | |
| exit 1 | |
| ;; | |
| esac | |
| done | |
| wait | |
| - name: "Save HF models cache" | |
| if: ( steps.changed-src-files.outputs.any_changed == 'true' && github.event_name != 'pull_request' && steps.cache_restore.outputs.cache-hit != 'true' ) | |
| uses: actions/cache/save@v4 | |
| with: | |
| path: ${{ env.model_path }} | |
| key: ${{ runner.os }}-hf-model-${{ env.model_key }} | |
| - name: "Run tests" | |
| if: steps.changed-src-files.outputs.any_changed == 'true' | |
| env: | |
| MASTER_PORT: 12355 | |
| MASTER_ADDR: localhost | |
| DISTRIBUTED_STRATEGY_IGNORE_MODULES: WordEmbedding | |
| VLLM_SPYRE_TEST_MODEL_LIST: "${{ matrix.test_suite.name == 'static batching' && 'JackFram/llama-160m' || '' }}" | |
| HF_HUB_OFFLINE: 1 | |
| run: | | |
| # Delete the source code so we can ensure we're testing the installed | |
| # wheel | |
| rm -fr vllm_spyre | |
| # We activate .venv manually and run pytest directly instead of using | |
| # `uv run`, to avoid having `uv run` re-sync any dependencies or | |
| # re-install the vllm_sypre package from source | |
| source .venv/bin/activate | |
| python3 -m pytest ${{ matrix.test_suite.flags }} \ | |
| tests -v -m "${{ matrix.test_suite.markers }}" |