Files
aszc-dev-ComfyUI-CoreMLSuite/docs/ci-m2.md
T
aszc-dev 29b493454a fix(phase4): init ComfyUI in place so a pre-seeded COMFY_DIR works
git clone refuses a non-empty target, so a COMFY_DIR pre-seeded with the
cached checkpoint (or converted .mlmodelc) would break setup. Replace clone
with git init + remote add + fetch + 'checkout -f', which populates the
ComfyUI tree without touching untracked files. Setup order is now free.
2026-05-25 15:49:07 +02:00

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# Self-hosted M2 runner — setup
Tier 2 (ANE + integration + bench) runs on a self-hosted GitHub Actions
runner registered against the maintainer's M-series Mac. Hosted macOS
runners on GitHub do not expose the Apple Neural Engine, so the ANE
half of the matrix has to live on real hardware.
## One-time runner setup
1. **Install dependencies on the Mac.** Python 3.12.x (matching the
`requires-python = ">=3.12,<3.13"` pin), `uv`, and `git`. The workflow
clones and manages the ComfyUI checkout itself (see step 3), so you do
not pre-install ComfyUI.
```bash
brew install python@3.12 uv git
```
2. **Register the runner.** From the repo Settings → Actions → Runners
→ New self-hosted runner, follow the macOS-ARM instructions. Add the
labels exactly: `self-hosted`, `macOS`, `ARM64`, `coreml` (the
workflow `runs-on` clause requires all four).
```bash
mkdir ~/actions-runner && cd ~/actions-runner
curl -O -L https://github.com/actions/runner/releases/download/v2.317.0/actions-runner-osx-arm64-2.317.0.tar.gz
tar xzf actions-runner-osx-arm64-2.317.0.tar.gz
./config.sh --url https://github.com/<owner>/<repo> \
--token <REGISTRATION_TOKEN> \
--labels self-hosted,macOS,ARM64,coreml \
--name "$(hostname)-m2"
./svc.sh install && ./svc.sh start # run as a launchd service
```
3. **Persist `COMFY_DIR` for the runner.** Point it at a **dedicated,
runner-owned** ComfyUI directory — **not** your personal dev checkout.
The workflow does `git reset --hard` on it and rewrites its
`custom_nodes/ComfyUI-CoreMLSuite` symlink, so it must be disposable.
Add it to the runner's `.env`:
```bash
echo 'COMFY_DIR=/Users/<you>/actions-runner/comfyui' >> ~/actions-runner/.env
```
You don't have to clone ComfyUI yourself: the `Set up ComfyUI checkout`
step clones it on first run, checks out the right ref (latest or the
pinned SHA — see *ComfyUI version under test*), installs ComfyUI's deps,
and symlinks `$COMFY_DIR/custom_nodes/ComfyUI-CoreMLSuite` →
`$GITHUB_WORKSPACE` so the server always loads the checked-out PR. If
`COMFY_DIR` is a real node directory rather than a symlink, the step
fails loudly instead of deleting it.
4. **Provide the SD1.5 checkpoint.** Drop
`v1-5-pruned-emaonly.safetensors` (~4 GB) into
`$COMFY_DIR/models/checkpoints/`. This is the one heavy artifact that
stays as a runner-local cache; everything derived from it (the
`.mlmodelc` UNet variants) is converted automatically by the
`Convert UNet variants if missing` step and cached across runs. Override
the filename with `CKPT_NAME` in the runner `.env` if needed.
Order is free: do this before or after the first run. The setup step
initialises the ComfyUI repo **in place** (`git init`, not `git clone`,
which would refuse a non-empty directory) and uses `checkout -f`, which
never removes untracked files — so a checkpoint you dropped in first is
preserved.
## Triggers
The Tier 2 workflow (`.github/workflows/tier2.yml`) runs:
- **On PR label `run-m2`** — maintainers add the label to opt a PR
into the ANE lane (the runner is not free; default off).
- **Nightly at 04:00 UTC** via `schedule:`.
- **Manually** via the workflow_dispatch button.
## ComfyUI version under test
Tier 2 runs a **hybrid** strategy, keyed on the trigger, so the suite tracks a
moving host without making PRs flaky to overnight upstream drift:
| Trigger | ComfyUI ref | ComfyUI deps |
|---|---|---|
| **schedule** (nightly) | latest `origin/master` | its own `requirements.txt`, capped by `constraints/comfy-ceiling.txt` |
| **PR label `run-m2`** / **dispatch** | pinned `requires-comfyui` SHA | the frozen `comfy` uv group |
- **Nightly = canary.** It pulls the latest ComfyUI and installs *ComfyUI's
own* dependency set. The frozen `comfy` uv group cannot track a moving host
by hand (a latest checkout needs e.g. `comfyui-frontend-package==1.44.19`,
`comfy_aimdo`, `alembic`, `blake3` that an older pin never listed), so latest
mode defers to upstream's `requirements.txt`. Upstream API or dependency
breakage surfaces here, in CI, instead of in a user's install.
- **PR / dispatch = reproducible gate.** It checks out the pinned
`requires-comfyui` SHA and uses the frozen `comfy` group — the known-good
combination — so a PR fails for its own reasons, not because ComfyUI moved.
The resolved ComfyUI SHA and mode are written to the job step summary (and
`COMFY_SHA` in the env), so any failure names the exact commit it hit.
**The toolchain ceiling is deliberate.** `constraints/comfy-ceiling.txt` caps
`torch<2.8` / `numpy<2` / `coremltools 9` while installing latest ComfyUI's
requirements. If upstream ever hard-requires something past those bounds the
nightly install *fails on purpose* — that is the signal that coremltools /
`ml-stable-diffusion` need a deliberate Phase-5-style bump, not a silent float
that would break the ANE path (see `docs/deps.md`).
`pyproject.toml`'s `requires-comfyui` is both the PR-gate ref and the
published-compatibility declaration for the Comfy registry. Bump it once a
newer ComfyUI is validated (the nightly canary is what tells you it's safe).
## Artifacts
- Bench JSON/MD are uploaded as `bench-results`.
- M2 golden image regressions surface as test failures in
`tests/m2/test_golden_image.py`; diff PNG is written next to the
golden under `tests/m2/_latest_generated.png` (gitignored).
## When the runner is down
If the maintainer's Mac is offline, the workflow queues until the
runner comes back. Cancel a stuck run from the Actions UI; the gate is
not blocking by default (Tier 0 + Tier 1 carry PR status). Tier 2 is
"good to merge once it goes green," not "blocked until then."
## Replacing the integration e2e
The legacy `tests/integration/test_basic_conversion_1_5.py` checked
CoreML output against an MPS reference image at PSNR > 25 dB. That
reference path is broken on macOS 26.x with torch 2.0.1 (see Phase 1
Gate report). Phase 4 moves the same coverage to
`tests/m2/test_golden_image.py`, which:
- runs the Core ML pipeline only (no MPS reference),
- asserts SHA256 against `tests/m2/goldens/sd15_seed42.sha256`,
- falls back to PSNR ≥ 40 dB if the hash drifts.
This removes the human-eyeball dependency: a regression is now a
numerical fail, not a "looks different to me."