name: macOS MLX Smoke

on:
  pull_request:
    branches: [main]
    paths:
      - ".github/workflows/ci-macos-mlx.yml"
      - "fastvideo/mlx_runtime/**"
      - "fastvideo/tests/mlx/**"
      - "fastvideo/tests/platforms/test_mps_vsa_error.py"
      - "fastvideo/platforms/mps.py"
      - "fastvideo/platforms/__init__.py"
      - "fastvideo/__init__.py"
      - "examples/inference/basic/mlx_*.py"
      - "fastvideo/benchmarks/mlx_*.py"
      - "pyproject.toml"
  workflow_dispatch:

permissions:
  contents: read

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

jobs:
  mlx-smoke:
    if: github.event_name == 'workflow_dispatch' || github.event.pull_request.draft != true
    runs-on: macos-15
    timeout-minutes: 25
    env:
      FASTVIDEO_ATTENTION_BACKEND: TORCH_SDPA
      TOKENIZERS_PARALLELISM: "false"
      MASTER_ADDR: localhost
      MASTER_PORT: "29513"
    steps:
      - uses: actions/checkout@v4

      - uses: actions/setup-python@v5
        with:
          python-version: "3.12"
          cache: pip

      - uses: astral-sh/setup-uv@v3

      - name: Install lightweight MLX smoke dependencies
        run: |
          uv pip install --system \
            --index-url https://download.pytorch.org/whl/cpu \
            torch==2.11.0 torchvision torchaudio
          uv pip install --system \
            pytest numpy scipy pillow imageio einops cloudpickle filelock \
            PyYAML diffusers huggingface_hub remote-pdb safetensors loguru mlx \
            "ftfy>=6.3.1" "opencv-python>=4.10.0.84" psutil "transformers>=5.0.0"

      - name: Show Apple runtime
        run: |
          python - <<'PY'
          import platform
          import mlx.core as mx
          import torch

          print("machine:", platform.machine())
          print("processor:", platform.processor())
          print("mlx default device:", mx.default_device())
          memory_size = mx.metal.device_info().get("memory_size") if mx.metal.is_available() else "metal unavailable"
          print("mlx memory_size:", memory_size)
          print("torch:", torch.__version__)
          print("torch mps available:", torch.backends.mps.is_available())
          PY

      - name: Run MLX smoke tests
        run: |
          python -m pytest \
            fastvideo/tests/mlx/test_dmd_sampling.py \
            fastvideo/tests/mlx/test_memory_limits.py \
            fastvideo/tests/mlx/test_quant_capability.py \
            fastvideo/tests/mlx/test_mlx_dit_parity.py \
            fastvideo/tests/mlx/test_mlx_compile_parity.py \
            fastvideo/tests/mlx/test_mlx_checkpoint.py \
            fastvideo/tests/mlx/test_mlx_fastwan_benchmark.py \
            fastvideo/tests/mlx/test_taehv_decode.py \
            fastvideo/tests/mlx/test_frame_upsample.py \
            fastvideo/tests/mlx/test_mlx_fast_spatial.py \
            fastvideo/tests/mlx/test_mlx_refine.py \
            fastvideo/tests/mlx/test_mlx_prompt_to_video_decode.py \
            fastvideo/tests/mlx/test_mlx_wan22_prompt_cache_fingerprint.py \
            fastvideo/tests/mlx/test_wan22_sample.py \
            fastvideo/tests/mlx/test_windowed_attention.py \
            fastvideo/tests/mlx/test_mlx_rife_interpolation.py::test_rife_download_unavailable_has_specific_error \
            fastvideo/tests/mlx/test_mlx_rife_interpolation.py::test_rife_backend_regression_is_not_skip_eligible \
            fastvideo/tests/platforms/test_mps_vsa_error.py \
            -q

  # Same tests on MLX's CPU backend. Hosted macOS runners are scarce and
  # slower to schedule; this Linux job gives fast PR signal on the identical
  # graph (the parity tests were designed to be backend-agnostic), while the
  # macOS job above stays the source of truth for Metal behavior.
  mlx-smoke-linux-cpu:
    if: github.event_name == 'workflow_dispatch' || github.event.pull_request.draft != true
    runs-on: ubuntu-latest
    timeout-minutes: 20
    env:
      FASTVIDEO_ATTENTION_BACKEND: TORCH_SDPA
      TOKENIZERS_PARALLELISM: "false"
      MASTER_ADDR: localhost
      MASTER_PORT: "29513"
    steps:
      - uses: actions/checkout@v4

      - uses: actions/setup-python@v5
        with:
          python-version: "3.12"
          cache: pip

      - uses: astral-sh/setup-uv@v3

      - name: Install lightweight MLX smoke dependencies (CPU backend)
        run: |
          uv pip install --system \
            --index-url https://download.pytorch.org/whl/cpu \
            torch==2.11.0 torchvision torchaudio
          uv pip install --system \
            pytest numpy scipy pillow imageio einops cloudpickle filelock \
            PyYAML diffusers huggingface_hub remote-pdb safetensors loguru "mlx[cpu]" \
            "ftfy>=6.3.1" "opencv-python>=4.10.0.84" psutil "transformers>=5.0.0"

      - name: Run MLX smoke tests (CPU backend)
        run: |
          python -m pytest \
            fastvideo/tests/mlx/test_dmd_sampling.py \
            fastvideo/tests/mlx/test_memory_limits.py \
            fastvideo/tests/mlx/test_quant_capability.py \
            fastvideo/tests/mlx/test_mlx_dit_parity.py \
            fastvideo/tests/mlx/test_mlx_compile_parity.py \
            fastvideo/tests/mlx/test_mlx_checkpoint.py \
            fastvideo/tests/mlx/test_mlx_fastwan_benchmark.py \
            fastvideo/tests/mlx/test_taehv_decode.py \
            fastvideo/tests/mlx/test_frame_upsample.py \
            fastvideo/tests/mlx/test_mlx_fast_spatial.py \
            fastvideo/tests/mlx/test_mlx_refine.py \
            fastvideo/tests/mlx/test_mlx_prompt_to_video_decode.py \
            fastvideo/tests/mlx/test_mlx_wan22_prompt_cache_fingerprint.py \
            fastvideo/tests/mlx/test_wan22_sample.py \
            fastvideo/tests/mlx/test_windowed_attention.py \
            fastvideo/tests/mlx/test_mlx_rife_interpolation.py::test_rife_download_unavailable_has_specific_error \
            fastvideo/tests/mlx/test_mlx_rife_interpolation.py::test_rife_backend_regression_is_not_skip_eligible \
            fastvideo/tests/platforms/test_mps_vsa_error.py \
            -q