dirghayu/.github/workflows/model-training.yml at main · VedantMadane/dirghayu · GitHub

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name: Train Models

# Run on schedule or manual trigger
on:
  workflow_dispatch:  # Manual trigger
    inputs:
      model_type:
        description: 'Model to train'
        required: true
        default: 'nutrient'
        type: choice
        options:
          - nutrient
          - pharmacogenomics
          - longevity
  schedule:
    - cron: '0 0 * * 0'  # Weekly on Sunday

jobs:
  train-cpu:
    name: Train Model (CPU)
    runs-on: ubuntu-latest

    steps:
    - uses: actions/checkout@v4

    - name: Install uv
      run: curl -LsSf https://astral.sh/uv/install.sh | sh

    - name: Set up Python
      uses: actions/setup-python@v5
      with:
        python-version: "3.11"

    - name: Install dependencies
      run: |
        export PATH="$HOME/.cargo/bin:$PATH"
        uv pip install --system -r requirements.txt

    - name: Download sample data
      run: python scripts/download_data.py

    - name: Train nutrient deficiency model
      run: |
        python -c "
        from src.models import NutrientPredictor
        from src.data import parse_vcf_file

        print('Training nutrient deficiency predictor...')
        predictor = NutrientPredictor()

        # Train on synthetic data (demo)
        variants_df = parse_vcf_file('data/sample.vcf')
        predictor.train(variants_df, None, epochs=10)
        predictor.save('models/nutrient_predictor.pth')

        print('✓ Model trained!')
        "

    - name: Upload trained model
      uses: actions/upload-artifact@v4
      with:
        name: trained-models
        path: models/*.pth
        retention-days: 30

  # CLOUD DEPLOYMENT - NOT RUN WITHOUT GCP CREDENTIALS
  # train-gpu:
  #   name: Train Model (GCP GPU)
  #   runs-on: ubuntu-latest
  #   if: github.event_name == 'workflow_dispatch'
  #
  #   steps:
  #   - uses: actions/checkout@v4
  #
  #   - name: Authenticate to GCP
  #     uses: google-github-actions/auth@v2
  #     with:
  #       credentials_json: ${{ secrets.GCP_SA_KEY }}
  #
  #   - name: Submit training job to GCP
  #     run: |
  #       gcloud ai custom-jobs create \
  #         --region=asia-southeast1 \
  #         --display-name=dirghayu-training \
  #         --worker-pool-spec=machine-type=n1-standard-4,accelerator-type=NVIDIA_TESLA_T4,accelerator-count=1,replica-count=1,container-image-uri=gcr.io/dirghayu/training:latest