NVIDIA PyTorch/CUDA Job #34
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| name: NVIDIA PyTorch/CUDA Job | |
| on: | |
| workflow_dispatch: | |
| inputs: | |
| script_content: | |
| description: 'Content of Python/CUDA script (.py or .cu file)' | |
| required: true | |
| type: string | |
| filename: | |
| description: 'Name of script (supports .py or .cu)' | |
| required: true | |
| type: string | |
| jobs: | |
| train: | |
| runs-on: [gpumode-nvidia-arc] | |
| timeout-minutes: 10 | |
| container: | |
| image: nvidia/cuda:12.4.0-devel-ubuntu22.04 | |
| steps: | |
| - name: Setup Python | |
| uses: actions/setup-python@v4 | |
| with: | |
| python-version: '3.10' | |
| - name: Install uv | |
| uses: astral-sh/setup-uv@v3 | |
| with: | |
| version: "latest" | |
| - name: Setup Python environment | |
| run: | | |
| uv venv .venv | |
| echo "VIRTUAL_ENV=$PWD/.venv" >> $GITHUB_ENV | |
| echo "$PWD/.venv/bin" >> $GITHUB_PATH | |
| - name: Create script | |
| shell: python | |
| run: | | |
| with open('${{ github.event.inputs.filename }}', 'w') as f: | |
| f.write('''${{ github.event.inputs.script_content }}''') | |
| - name: Install dependencies and setup NVCC | |
| run: | | |
| # Check for PyTorch | |
| if grep -rE "(import torch|from torch)" "${{ github.event.inputs.filename }}"; then | |
| echo "PyTorch detected, installing torch" | |
| uv pip install numpy torch | |
| fi | |
| # Check for Triton | |
| if grep -rE "(import triton|from triton)" "${{ github.event.inputs.filename }}"; then | |
| echo "Triton detected, installing triton" | |
| uv pip install triton | |
| fi | |
| - name: Run script with profiler | |
| run: | | |
| if [[ "${{ github.event.inputs.filename }}" == *.cu ]]; then | |
| # Compile and run CUDA file | |
| nvcc "${{ github.event.inputs.filename }}" -o cuda_program | |
| ./cuda_program > training.log 2>&1 | |
| else | |
| # Run Python file | |
| python "${{ github.event.inputs.filename }}" > training.log 2>&1 | |
| fi | |
| - name: Upload training artifacts | |
| uses: actions/upload-artifact@v4 | |
| if: always() | |
| with: | |
| name: training-artifacts | |
| path: | | |
| training.log | |
| # profile_results.csv | |
| ${{ github.event.inputs.filename }} | |
| cuda_program* | |
| env: | |
| CUDA_VISIBLE_DEVICES: 0 # Make sure only one GPU is used for testing |