Call remote LLM Engine for funcs of model_setup and timer_summary. #556
Workflow file for this run
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| name: Unit Tests | |
| on: | |
| workflow_dispatch: | |
| pull_request: | |
| branches: | |
| - main | |
| - dev | |
| paths-ignore: | |
| - 'docs/**' | |
| push: | |
| branches: | |
| - main | |
| paths-ignore: | |
| - 'docs/**' | |
| tags: | |
| - v[0-9]+.[0-9]+.[0-9]+ | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }} | |
| cancel-in-progress: true | |
| jobs: | |
| run-shell-script: | |
| runs-on: self-hosted | |
| steps: | |
| - name: Checkout code | |
| uses: actions/checkout@v4 | |
| - name: Run unit test | |
| run: | | |
| containers=$(docker ps -aqf "name=^chatlearn_ut_") | |
| if [[ -n "$containers" ]]; then | |
| docker rm $containers -f | |
| fi | |
| docker pull $UT_IMAGE | |
| docker run -v $PWD:$PWD -w $PWD --name chatlearn_ut_$(date '+%d_%m_%Y_%H_%M_%S') --net host --ipc host --shm-size 80G -t --rm --gpus all $UT_IMAGE bash -c 'make test' | |
| env: | |
| UT_IMAGE: registry.cn-wulanchabu.aliyuncs.com/pai-dlc/pytorch-training:2.4.0-gpu-py3.10-cu12.5-ngc24.06-ubuntu22.04 |