NVIDIA PyTorch/CUDA Job #25
This file contains 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: 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] | |
| 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: 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: | | |
| # Check if 'import torch' is in any Python file | |
| if grep -rE "(import torch|from torch)" "${{ github.event.inputs.filename }}"; then | |
| echo "PyTorch detected, installing torch" | |
| uv pip install numpy torch | |
| fi | |
| # Check if 'import triton' is in any Python file | |
| if grep -rE "(import triton|from triton)" "${{ github.event.inputs.filename }}"; then | |
| echo "Triton detected, installing triton" | |
| uv pip install triton | |
| fi | |
| - name: Run script with profiler | |
| run: | | |
| # Run the script with NSight Compute profiler and save to CSV | |
| # ncu --csv python "${{ github.event.inputs.filename }}" > profile_results.csv 2>&1 | |
| # Also keep regular output in training.log | |
| python "${{ github.event.inputs.filename }}" > training.log 2>&1 | |
| - 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 }} | |
| env: | |
| CUDA_VISIBLE_DEVICES: 0 # Make sure only one GPU is used for testing |