train_workflow.yml

name: Training Workflow
on:
  workflow_dispatch:
    inputs:
      script_content:
        description: 'Content of training script (Python or CUDA)'
        required: true
        type: string
      script_type:
        description: 'Script type (py or cu)'
        required: true
        type: choice
        options:
          - py
          - cu

jobs:
  train:
    runs-on: ubuntu-latest
    steps:
      - name: Set up environment variables
        run: |
          echo "SCRIPT_FILE=train.${{ inputs.script_type }}" >> $GITHUB_ENV
          echo "OUTPUT_FILE=training.log" >> $GITHUB_ENV

      - name: Install Python dependencies
        if: inputs.script_type == 'py'
        run: |
          pip install numpy
          # Add other Python dependencies as needed

      - name: Install CUDA dependencies
        if: inputs.script_type == 'cu'
        run: |
          sudo apt-get update
          sudo apt-get install -y nvidia-cuda-toolkit
          nvcc --version

      - name: Create training script
        run: |
          echo "${{ inputs.script_content }}" > ${{ env.SCRIPT_FILE }}
          cat ${{ env.SCRIPT_FILE }}  # Debug: print the content

      - name: Compile and run CUDA script
        if: inputs.script_type == 'cu'
        run: |
          nvcc ${{ env.SCRIPT_FILE }} -o train_cuda
          ./train_cuda > ${{ env.OUTPUT_FILE }} 2>&1

      - name: Run Python script
        if: inputs.script_type == 'py'
        run: |
          python ${{ env.SCRIPT_FILE }} > ${{ env.OUTPUT_FILE }} 2>&1

      - name: Upload logs
        uses: actions/upload-artifact@v3
        if: always()
        with:
          name: training-logs
          path: ${{ env.OUTPUT_FILE }}