Roformer.cpp/.github/workflows/build.yml

name: CI

on:
  push:
    branches: [main, master]
    paths:
      - '**/*.cpp'
      - '**/*.h'
      - '**/*.hpp'
      - '**/CMakeLists.txt'
      - '.github/workflows/**'
  pull_request:
    types: [opened, synchronize, reopened]
  workflow_dispatch:

concurrency:
  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
  cancel-in-progress: true

env:
  # HuggingFace model info
  HF_MODEL_REPO: GaboxR67/MelBandRoformers
  HF_CHECKPOINT_PATH: melbandroformers/vocals/voc_fv6.ckpt
  HF_CONFIG_PATH: melbandroformers/vocals/voc_gabox.yaml
  # Music-Source-Separation-Training repo
  MSST_REPO: https://github.com/ZFTurbo/Music-Source-Separation-Training.git

jobs:
  # ===========================================================================
  # Prepare: Generate test data (runs once, shared via artifacts)
  # ===========================================================================
  prepare-test-data:
    runs-on: ubuntu-latest
    
    steps:
      - name: Checkout
        uses: actions/checkout@v4
      
      - name: Setup Python
        uses: actions/setup-python@v5
        with:
          python-version: '3.11'
          
      - name: Clone MSST Repository
        run: git clone --depth 1 ${{ env.MSST_REPO }} msst
        
      - name: Install Dependencies
        run: |
          pip install torch torchaudio --index-url https://download.pytorch.org/whl/cpu
          pip install huggingface_hub scipy soundfile gguf librosa ml_collections einops pyyaml numpy tqdm beartype rotary_embedding_torch
          
      - name: Download Model from HuggingFace
        env:
          HF_TOKEN: ${{ secrets.HF_TOKEN }}
        run: |
          python -c "
          from huggingface_hub import hf_hub_download
          import os
          token = os.environ.get('HF_TOKEN') or None
          hf_hub_download('${{ env.HF_MODEL_REPO }}', '${{ env.HF_CHECKPOINT_PATH }}', 
                          local_dir='./model', token=token)
          hf_hub_download('${{ env.HF_MODEL_REPO }}', '${{ env.HF_CONFIG_PATH }}',
                          local_dir='./model', token=token)
          "
          
      - name: Generate Test Audio
        run: |
          python -c "
          import numpy as np
          import scipy.io.wavfile as wav
          sr = 44100
          duration = 5.0
          t = np.linspace(0, duration, int(sr * duration))
          # Create a more complex test signal
          left = (np.sin(2 * np.pi * 440 * t) + 0.5 * np.sin(2 * np.pi * 880 * t)) * 0.3
          right = (np.sin(2 * np.pi * 660 * t) + 0.5 * np.sin(2 * np.pi * 1320 * t)) * 0.3
          stereo = np.stack([left, right], axis=1).astype(np.float32)
          wav.write('test_audio.wav', sr, stereo)
          print(f'Generated test audio: {len(t)} samples, {duration}s')
          "
          
      - name: Generate Test Data
        run: |
          python scripts/generate_test_data.py \
            --model-repo msst \
            --audio test_audio.wav \
            --checkpoint model/${{ env.HF_CHECKPOINT_PATH }} \
            --config model/${{ env.HF_CONFIG_PATH }} \
            --output test_data
            
      - name: Convert Model to GGUF
        run: |
          python scripts/convert_to_gguf.py \
            --ckpt model/${{ env.HF_CHECKPOINT_PATH }} \
            --config model/${{ env.HF_CONFIG_PATH }} \
            --out model.gguf \
            --dtype fp16
            
      - name: Upload Test Data Artifact
        uses: actions/upload-artifact@v4
        with:
          name: test-data
          path: |
            test_data/
            model.gguf
            test_audio.wav
          retention-days: 1

  # ===========================================================================
  # Build Matrix: Core Platforms + Vulkan
  # ===========================================================================
  build:
    needs: prepare-test-data
    strategy:
      fail-fast: false
      matrix:
        include:
          # Tier 1: Core Platforms (CPU)
          - { name: linux-x64-cpu,    os: ubuntu-22.04,     backend: cpu,    test: true  }
          - { name: linux-arm64-cpu,  os: ubuntu-22.04-arm, backend: cpu,    test: true  }
          - { name: macos-arm64,      os: macos-latest,     backend: cpu,    test: true  }
          - { name: macos-x64,        os: macos-15-intel,   backend: cpu,    test: true  }
          - { name: windows-x64-msvc, os: windows-2025,     backend: cpu,    test: true  }
          # Tier 2: Vulkan Backend
          - { name: linux-vulkan,     os: ubuntu-24.04,     backend: vulkan, test: true  }
          - { name: windows-vulkan,   os: windows-2025,     backend: vulkan, test: true  }
          
    runs-on: ${{ matrix.os }}
    
    steps:
      - name: Checkout
        uses: actions/checkout@v4
      
      - name: Clone GGML
        run: git clone --depth 1 https://github.com/ggerganov/ggml.git ggml
      
      - name: Download Test Data
        uses: actions/download-artifact@v4
        with:
          name: test-data
          
      - name: Setup Python
        uses: actions/setup-python@v5
        with:
          python-version: '3.11'
          
      - name: Install Python Dependencies
        run: pip install numpy scipy
          
      # ----- Linux Dependencies -----
      - name: Install Dependencies (Linux)
        if: runner.os == 'Linux'
        run: |
          sudo apt-get update
          sudo apt-get install -y build-essential cmake
          
      - name: Install Vulkan SDK (Linux)
        if: matrix.backend == 'vulkan' && runner.os == 'Linux'
        run: |
          sudo apt-get install -y libvulkan-dev glslc mesa-vulkan-drivers
          
      # ----- macOS Dependencies -----  
      - name: Install Dependencies (macOS)
        if: runner.os == 'macOS'
        run: brew install cmake
        
      # ----- Windows Dependencies -----
      - name: Install Dependencies (Windows)
        if: runner.os == 'Windows'
        run: choco install ninja -y
        
      - name: Install Vulkan SDK (Windows)
        if: matrix.backend == 'vulkan' && runner.os == 'Windows'
        run: |
          $VK_VERSION = "1.4.313.2"
          curl.exe -o VulkanSDK.exe -L "https://sdk.lunarg.com/sdk/download/${VK_VERSION}/windows/vulkansdk-windows-X64-${VK_VERSION}.exe"
          Start-Process -FilePath .\VulkanSDK.exe -ArgumentList "--accept-licenses --default-answer --confirm-command install" -Wait
          Add-Content $env:GITHUB_ENV "VULKAN_SDK=C:\VulkanSDK\${VK_VERSION}"
          Add-Content $env:GITHUB_PATH "C:\VulkanSDK\${VK_VERSION}\bin"
          
      # ----- Configure -----
      - name: Configure (Unix)
        if: runner.os != 'Windows'
        run: |
          cmake -B build \
            -DCMAKE_BUILD_TYPE=Release \
            -DGGML_DIR=ggml \
            -DGGML_CUDA=OFF \
            -DGGML_VULKAN=${{ matrix.backend == 'vulkan' && 'ON' || 'OFF' }} \
            -DMBR_BUILD_TESTS=ON \
            -DMBR_BUILD_CLI=ON
            
      - name: Configure (Windows)
        if: runner.os == 'Windows'
        run: |
          cmake -B build -G "Ninja Multi-Config" `
            -DGGML_DIR=ggml `
            -DGGML_CUDA=OFF `
            -DGGML_VULKAN=${{ matrix.backend == 'vulkan' && 'ON' || 'OFF' }} `
            -DMBR_BUILD_TESTS=ON `
            -DMBR_BUILD_CLI=ON
            
      # ----- Build -----
      - name: Build (Unix)
        if: runner.os != 'Windows'
        run: cmake --build build --config Release -j $(nproc 2>/dev/null || sysctl -n hw.logicalcpu)
        
      - name: Build (Windows)
        if: runner.os == 'Windows'
        run: cmake --build build --config Release -j $env:NUMBER_OF_PROCESSORS
        
      # ----- Unit Tests -----
      - name: Run Unit Tests
        if: matrix.test
        env:
          MBR_MODEL_PATH: ${{ github.workspace }}/model.gguf
          MBR_TEST_DATA_DIR: ${{ github.workspace }}/test_data
        run: ctest --test-dir build -C Release --output-on-failure --timeout 300
        
      # ----- CLI Tests -----
      - name: Test CLI
        if: matrix.test
        shell: bash
        env:
          MBR_MODEL_PATH: ${{ github.workspace }}/model.gguf
        run: |
          echo "=== CLI Test Suite ==="
          
          # Determine CLI path based on OS
          if [[ "$RUNNER_OS" == "Windows" ]]; then
            CLI="./build/bin/Release/mel_band_roformer-cli.exe"
          else
            CLI="./build/mel_band_roformer-cli"
          fi
          
          # 1. Test --help
          echo "[1/4] Testing --help..."
          $CLI --help
          
          # 2. Test with missing arguments (should fail)
          echo "[2/4] Testing error handling..."
          if $CLI 2>/dev/null; then
            echo "ERROR: CLI should fail without arguments"
            exit 1
          fi
          
          # 3. Generate test audio (short 2-second clip)
          echo "[3/4] Generating test audio..."
          python3 -c "
          import numpy as np
          import scipy.io.wavfile as wav
          sr = 44100
          t = np.linspace(0, 2.0, sr * 2)
          stereo = np.stack([np.sin(2*np.pi*440*t), np.sin(2*np.pi*880*t)], axis=1).astype(np.float32) * 0.5
          wav.write('cli_test_input.wav', sr, stereo)
          "
          
          # 4. Run full inference
          echo "[4/4] Running inference..."
          $CLI "$MBR_MODEL_PATH" cli_test_input.wav cli_test_output.wav --chunk-size 88200 --overlap 2
          
          # Verify output exists and has reasonable size
          if [[ ! -f cli_test_output.wav ]]; then
            echo "ERROR: Output file not created"
            exit 1
          fi
          
          OUTPUT_SIZE=$(stat -c%s cli_test_output.wav 2>/dev/null || stat -f%z cli_test_output.wav)
          if [[ $OUTPUT_SIZE -lt 1000 ]]; then
            echo "ERROR: Output file too small: $OUTPUT_SIZE bytes"
            exit 1
          fi
          
          echo "=== CLI Tests Passed ==="
          
      # ----- Upload Artifacts -----
      - name: Upload Build Artifacts
        uses: actions/upload-artifact@v4
        with:
          name: build-${{ matrix.name }}
          path: |
            build/bin/
            build/lib*/
            build/*.dll
            build/*.so
            build/*.dylib
            build/mel_band_roformer-cli*
            build/Release/
          retention-days: 7

  # ===========================================================================
  # CUDA Build: Linux (Compile Only - No GPU for testing)
  # ===========================================================================
  build-cuda-linux:
    runs-on: ubuntu-latest
    container: nvidia/cuda:12.6.2-devel-ubuntu24.04
    
    steps:
      - name: Install Git
        run: |
          apt-get update
          apt-get install -y git
          
      - name: Checkout
        uses: actions/checkout@v4
      
      - name: Clone GGML
        run: git clone --depth 1 https://github.com/ggerganov/ggml.git ggml
      
      - name: Install Dependencies
        run: |
          apt-get install -y cmake build-essential ninja-build
          
      - name: Configure
        run: |
          ls -ld ggml
          cmake -B build -G Ninja \
            -DCMAKE_BUILD_TYPE=Release \
            -DGGML_DIR=ggml \
            -DGGML_CUDA=ON \
            -DCMAKE_CUDA_ARCHITECTURES="75;80;86;89" \
            -DMBR_BUILD_TESTS=OFF \
            -DMBR_BUILD_CLI=ON
            
      - name: Build
        run: cmake --build build --config Release -j $(nproc)
        
      - name: Upload Artifacts
        uses: actions/upload-artifact@v4
        with:
          name: build-linux-cuda
          path: |
            build/bin/
            build/lib*/
            build/*.so
          retention-days: 7

  # ===========================================================================
  # CUDA Build: Windows (Compile Only - No GPU for testing)
  # ===========================================================================
  build-cuda-windows:
    runs-on: windows-2022
    
    env:
      CUDA_VERSION: '12.4'
    
    steps:
      - name: Checkout
        uses: actions/checkout@v4
      
      - name: Clone GGML
        run: git clone --depth 1 https://github.com/ggerganov/ggml.git ggml
      
      - name: Install CUDA Toolkit
        run: |
          # For CI, use the official CUDA installer approach
          curl.exe -o cuda_installer.exe -L "https://developer.download.nvidia.com/compute/cuda/12.4.0/network_installers/cuda_12.4.0_windows_network.exe"
          Start-Process -FilePath .\cuda_installer.exe -ArgumentList "-s nvcc_12.4 cudart_12.4 cublas_12.4 cublas_dev_12.4 cufft_12.4 cufft_dev_12.4" -Wait -NoNewWindow
          Add-Content $env:GITHUB_ENV "CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4"
          Add-Content $env:GITHUB_PATH "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4\bin"
        
      - name: Install Ninja
        run: choco install ninja -y
        
      - name: Configure
        shell: cmd
        run: |
          call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64
          cmake -B build -G "Ninja Multi-Config" ^
            -DGGML_DIR=ggml ^
            -DGGML_CUDA=ON ^
            -DCMAKE_CUDA_ARCHITECTURES="75;80;86;89" ^
            -DMBR_BUILD_TESTS=OFF ^
            -DMBR_BUILD_CLI=ON
            
      - name: Build
        run: cmake --build build --config Release -j $env:NUMBER_OF_PROCESSORS
        
      - name: Upload Artifacts
        uses: actions/upload-artifact@v4
        with:
          name: build-windows-cuda
          path: |
            build/bin/
            build/Release/
            build/*.dll
          retention-days: 7