name: Nightly Tests

on:
  workflow_dispatch:
  schedule:
    # Every day at 02:15 AM UTC
    - cron: "15 2 * * *"

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

jobs:
  test-cpu:
    name: CPU
    if: github.repository == 'bitsandbytes-foundation/bitsandbytes'
    strategy:
      fail-fast: false
      matrix:
        platform: [linux-x64, linux-aarch64, macos, windows, windows-arm64]
        # default runners don't have AVX-512 support, but icelake does
        cpu_type: ["", icelake]
        torch_version: ["2.4.1", "2.12.0", "2.13.0", "nightly"]

        exclude:
          # aarch64 minimum torch version is 2.5.1
          - platform: linux-aarch64
            torch_version: "2.4.1"
          # icelake only applies to linux-x64
          - platform: linux-aarch64
            cpu_type: icelake
          - platform: macos
            cpu_type: icelake
          - platform: windows
            cpu_type: icelake
          - platform: windows-arm64
            cpu_type: icelake
          # windows-arm64: torch >= 2.7.0 required (first version with official WoA wheels)
          - platform: windows-arm64
            torch_version: "2.4.1"

        include:
          # Add aarch64 with torch 2.5.1
          - platform: linux-aarch64
            cpu_type: ""
            torch_version: "2.5.1"
          # Add windows-arm64 with minimum torch 2.7.1
          - platform: windows-arm64
            cpu_type: ""
            torch_version: "2.7.1"

    uses: ./.github/workflows/test-runner.yml
    with:
      platform: ${{ matrix.platform }}
      backend: cpu
      torch_version: ${{ matrix.torch_version }}
      pypi_index: ${{ matrix.torch_version == 'nightly' && 'https://download.pytorch.org/whl/nightly/cpu' || 'https://download.pytorch.org/whl/cpu' }}
      cpu_type: ${{ matrix.cpu_type }}

  test-cuda:
    name: CUDA ${{ matrix.cuda_version }} (${{ matrix.platform }}, ${{ matrix.gpu_type }}, ${{ matrix.torch_version }})
    if: github.repository == 'bitsandbytes-foundation/bitsandbytes'
    strategy:
      fail-fast: false
      matrix:
        # Linux x64 cross-product
        platform: [linux-x64]
        gpu_type: [T4, A10, L40S]
        cuda_version: ["11.8.0", "12.6.3", "12.8.1", "13.0.2", "13.2.0"]

        include:
          # Map CUDA version to torch version and PyPI index
          - cuda_version: "11.8.0"
            torch_version: "2.4.1"
            pypi_index: "https://download.pytorch.org/whl/cu118"
          - cuda_version: "12.6.3"
            torch_version: "2.12.0"
            pypi_index: "https://download.pytorch.org/whl/cu126"
          - cuda_version: "12.8.1"
            torch_version: "2.11.0"
            pypi_index: "https://download.pytorch.org/whl/cu128"
          - cuda_version: "13.0.2"
            torch_version: "2.13.0"
            pypi_index: "https://download.pytorch.org/whl/cu130"
          - cuda_version: "13.2.0"
            torch_version: "nightly"
            pypi_index: "https://download.pytorch.org/whl/nightly/cu132"

          # Windows CUDA Tests - T4 GPU (CUDA 11.8 only, multiple torch versions)
          - platform: windows
            gpu_type: T4
            cuda_version: "11.8.0"
            torch_version: "2.4.1"
            pypi_index: "https://download.pytorch.org/whl/cu118"
          - platform: windows
            gpu_type: T4
            cuda_version: "11.8.0"
            torch_version: "2.6.0"
            pypi_index: "https://download.pytorch.org/whl/cu118"
          - platform: windows
            gpu_type: T4
            cuda_version: "11.8.0"
            torch_version: "2.7.1"  # Note: this is the last PyTorch release supporting CUDA 11.8.
            pypi_index: "https://download.pytorch.org/whl/cu118"

    uses: ./.github/workflows/test-runner.yml
    with:
      platform: ${{ matrix.platform }}
      backend: cuda
      cuda_version: ${{ matrix.cuda_version }}
      gpu_type: ${{ matrix.gpu_type }}
      torch_version: ${{ matrix.torch_version }}
      pypi_index: ${{ matrix.pypi_index }}