ci.yml

name: CI

on:
  pull_request:

permissions:
  contents: read

concurrency:
  group: ci-${{ github.ref }}
  cancel-in-progress: true

jobs:
  build-and-test:
    runs-on: ubuntu-latest
    timeout-minutes: 30
    env:
      OMP_NUM_THREADS: 1
    steps:
      - name: Checkout
        uses: actions/checkout@v4

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

      - name: Install system deps
        run: |
          sudo apt-get update
          sudo apt-get install -y git

      - name: Set up venv
        run: |
          python -m venv .venv
          source .venv/bin/activate
          python -m pip install -U pip
          python -m pip install -r requirements.txt || true
          # Ensure CPU-only PyTorch is available in CI
          pip install --extra-index-url https://download.pytorch.org/whl/cpu torch torchvision torchaudio || true

      - name: Quick smoke test (example dataset)
        run: |
          source .venv/bin/activate
          python train_model.py

      - name: Prepare dataset (download if missing)
        env:
          DATA_DIR: ${{ github.workspace }}/dataset/trendy1
        run: |
          chmod +x scripts/prepare_data.sh
          bash scripts/prepare_data.sh "$DATA_DIR"

      - name: CNP training smoke test (dataset, 1 file, 1 epoch)
        env:
          DATA_DIR: ${{ github.workspace }}/dataset/trendy1
        run: |
          source .venv/bin/activate
          python train_cnp_model.py \
            --epoch 1 \
            --variable-list ./CNP_IO_updated9_dev.txt \
            --mask-absent-pfts \
            --model-config ./CNP_model_config_v01.txt \
            --use-trendy1 \
            --data-paths "$DATA_DIR" \
            --file-pattern 'enhanced_1_training_data_batch_*.pkl' \
            --max-files 1

      - name: CNP training config validation (no data)
        run: |
          source .venv/bin/activate
          python train_cnp_model.py --config-only --use-trendy1 --epoch 1 --batch-size 8