Test model fast workflow (microsoft/Olive)
The Test model fast workflow from microsoft/Olive, explained and optimized by Latchkey.
CI health: D - needs work
Point runs-on at Latchkey and get caching, run de-duplication, job timeouts, self-healing for flaky steps, and up to 58% lower cost, applied automatically.
What it does
This is the Test model fast workflow from the microsoft/Olive repository, a real project running GitHub Actions. It is shown here with attribution under its MIT license.
Below, Latchkey shows a faster, safer version produced by its optimization engine.
The workflow
# This job is run as a github action.
# It checks Olive works on random and small models.
name: Test model fast
on:
workflow_dispatch:
push:
branches:
- main
pull_request:
branches:
- main
jobs:
ubuntu-test-model-fast:
name: Ubuntu test model fast
runs-on: ubuntu-latest
permissions:
contents: read
steps:
- uses: actions/checkout@v4
- name: Setup Python
uses: actions/setup-python@v5
with:
python-version: "3.12"
- name: Install dependencies
run: |
python -m pip install -r requirements.txt
python -m pip install -r test/requirements-test-cpu.txt
- name: Create llama_env and install llama-cpp-python
run: |
LLAMA_ENV="$(pwd)/llama_env"
python -m venv "$LLAMA_ENV"
"$LLAMA_ENV/bin/pip" install --upgrade pip
"$LLAMA_ENV/bin/pip" install gguf safetensors llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cpu
"$LLAMA_ENV/bin/pip" install transformers sentencepiece protobuf tabulate gguf
git clone --depth=1 --filter=blob:none --sparse https://github.com/ggerganov/llama.cpp.git /tmp/llama_cpp_repo
git -C /tmp/llama_cpp_repo sparse-checkout set convert_hf_to_gguf.py conversion --skip-checks
cp /tmp/llama_cpp_repo/convert_hf_to_gguf.py "$LLAMA_ENV/"
cp -r /tmp/llama_cpp_repo/conversion "$LLAMA_ENV/"
- name: pip freeze
run: |
python -m pip freeze
- name: Run fast test
run: |
python -m pytest -v -s -p no:warnings --disable-warnings --log-cli-level=WARNING test/cli/test_cli_test_model_smoke.py test/cli/test_cli_whisper_smoke.py
The same workflow, on Latchkey
Estimated ~20% faster on cache hits, plus fewer wasted runs and a safer supply chain. Added and changed lines are highlighted.
# This job is run as a github action. # It checks Olive works on random and small models. name: Test model fast on: workflow_dispatch: push: branches: - main pull_request: branches: - main concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: true jobs: ubuntu-test-model-fast: timeout-minutes: 30 name: Ubuntu test model fast runs-on: latchkey-small permissions: contents: read steps: - uses: actions/checkout@v4 - name: Setup Python uses: actions/setup-python@v5 with: cache: 'pip' python-version: "3.12" - name: Install dependencies run: | python -m pip install -r requirements.txt python -m pip install -r test/requirements-test-cpu.txt - name: Create llama_env and install llama-cpp-python run: | LLAMA_ENV="$(pwd)/llama_env" python -m venv "$LLAMA_ENV" "$LLAMA_ENV/bin/pip" install --upgrade pip "$LLAMA_ENV/bin/pip" install gguf safetensors llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cpu "$LLAMA_ENV/bin/pip" install transformers sentencepiece protobuf tabulate gguf git clone --depth=1 --filter=blob:none --sparse https://github.com/ggerganov/llama.cpp.git /tmp/llama_cpp_repo git -C /tmp/llama_cpp_repo sparse-checkout set convert_hf_to_gguf.py conversion --skip-checks cp /tmp/llama_cpp_repo/convert_hf_to_gguf.py "$LLAMA_ENV/" cp -r /tmp/llama_cpp_repo/conversion "$LLAMA_ENV/" - name: pip freeze run: | python -m pip freeze - name: Run fast test run: | python -m pytest -v -s -p no:warnings --disable-warnings --log-cli-level=WARNING test/cli/test_cli_test_model_smoke.py test/cli/test_cli_whisper_smoke.py
What changed
- Run on Latchkey managed runners with one line (
runs-on), which apply the fixes below automatically and self-heal transient failures. This example useslatchkey-small; pick the runner size that fits the job. - Cancel superseded runs when a branch or PR gets a newer push.
- Cache dependency installs on the setup step so they are served from cache.
- Add a job timeout so a hung step cannot burn hours of runner time.
What Latchkey heals here
This workflow has steps that commonly fail on transient issues (network, registries, flaky browsers). On Latchkey managed runners they are detected, retried, and self-healed instead of failing your build:
- Dependency installs
This workflow runs 1 job per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.