NVIDIA PyTorch/CUDA Job #2
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| name: NVIDIA PyTorch Job | |
| on: | |
| workflow_dispatch: | |
| inputs: | |
| script_content: | |
| description: 'Content of Python script' | |
| required: true | |
| type: string | |
| filename: | |
| description: 'Name of Python script' | |
| required: true | |
| type: string | |
| jobs: | |
| train: | |
| runs-on: [gpumode-nvidia-arc] | |
| 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: Create script | |
| shell: python | |
| run: | | |
| with open('${{ github.event.inputs.filename }}', 'w') as f: | |
| f.write('''${{ github.event.inputs.script_content }}''') | |
| - name: Install dependencies | |
| run: | | |
| if grep -rE "(import numpy|from numpy)" "${{ github.event.inputs.filename }}"; then | |
| echo "Numpy detected, installing numpy" | |
| pip install numpy | |
| fi | |
| # Check if 'import torch' is in any Python file | |
| if grep -rE "(import torch|from torch)" "${{ github.event.inputs.filename }}"; then | |
| echo "PyTorch detected, installing torch" | |
| pip install torch | |
| fi | |
| # Check if 'import triton' is in any Python file | |
| if grep -rE "(import triton|from triton)" "${{ github.event.inputs.filename }}"; then | |
| echo "Triton detected, installing triton" | |
| pip install triton | |
| fi | |
| - name: Run script with NSight Compute profiling | |
| run: | | |
| # First run normally and capture output | |
| python "${{ github.event.inputs.filename }}" > training.log 2>&1 | |
| # Then run with NSight Compute profiling | |
| ncu --set full --export ncu_profile "${{ github.event.inputs.filename }}" > ncu.log 2>&1 | |
| - name: Upload training artifacts | |
| uses: actions/upload-artifact@v3 | |
| if: always() | |
| with: | |
| name: training-artifacts | |
| path: | | |
| training.log | |
| ${{ github.event.inputs.filename }} | |
| - name: Upload NSight Compute artifacts | |
| uses: actions/upload-artifact@v3 | |
| if: always() | |
| with: | |
| name: ncu-artifacts | |
| path: | | |
| ncu.log | |
| ncu_profile.ncu-rep | |
| env: | |
| CUDA_VISIBLE_DEVICES: 0 # Make sure only one GPU is used for testing |