Files
DarkRoom/docs/dev/macos.md
T
dtourolle c73743394f Add a CoreML rung on macOS
The macOS ladder was the CPU provider alone, with CoreML listed as a gap.
It is now CoreML, then the CPU, then tract — unmeasured, since nobody here
has a Mac, and safe to ship unmeasured because the probe's clock rejects a
CoreML slower than the CPU and `attempt` refuses one that crashes.

- `Rung::CoreMl`, a compiling rung like TensorRT: an ML Program with every
  compute unit allowed, falling back to the CPU until each model's program
  is built. The embedder stays on the CPU, as on the Hexagon (§7).
- The cache is one directory per model and runtime version. CoreML keys a
  model committed from memory on its input and node names, not its
  weights (ONNX Runtime 1.29, coreml_execution_provider.cc), so two
  exports of one architecture would otherwise share a program.
- The fingerprint on macOS is the chip and the OS release, which ships
  CoreML.
- The desktop looks for the runtime in the bundle's Contents/Frameworks
  and Homebrew's prefixes; fetch-desktop-runtime.sh on a Mac downloads
  ONNX Runtime 1.29.0 for Apple silicon, which carries CoreML.

docs/dev/macos.md says what exists, how to build it, and which log lines
to ask a Mac user for.
2026-10-03 16:50:37 -04:00

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# macOS
macOS is out of scope for v1 ([requirements.md](requirements.md)), and nobody working on
DarkRoom has a Mac. This page records what exists anyway, and how a macOS build is set up so
that someone who does have one can send back enough to fix what they hit.
## 1. What exists
- **Inference** ([inference.md §2](inference.md)). The macOS ladder is CoreML, then ONNX
Runtime's CPU provider, then tract. CoreML is unmeasured. The probe decides whether it is used,
and the crash guard (§4, `attempt`) covers the case where the provider takes the process down.
The device fingerprint is the chip (`machdep.cpu.brand_string`) and the OS release, because
CoreML ships with the OS.
- **Where files go** ([`dr_plat::dirs`](../../platform/dr-plat/src/dirs.rs)). The Unix rules,
except the state directory (the log and crash records), which is `~/Library/Logs/darkroom`.
- **A diagnostic build**, described in §3.
The rest is not built, packaged or run on macOS by anyone here. This covers the window,
Metal through wgpu, the display profile (FR-DSP-8 asks X11 and Wayland), the keyring, the
bundle, and signing. `dr-plat` sends every non-Android Unix to the X11/Wayland dependencies.
## 2. Building
The Rust side compile-checks from Linux:
rustup target add aarch64-apple-darwin
cargo check --target aarch64-apple-darwin -p dr-inference-engine --features native
Linking needs Apple's SDK, which means a Mac. On one:
cargo build --profile diagnostic -p darkroom-desktop
./tools/fetch-desktop-runtime.sh # ONNX Runtime 1.29.0 with CoreML, Apple silicon only
The fetch script puts `libonnxruntime.dylib` in the user's `runtime/` directory, next to the
models. The app also looks in `Contents/Frameworks` of its own bundle, and in Homebrew's
`/opt/homebrew/lib` and `/usr/local/lib`. Homebrew's build may not include CoreML; the probe
reports that as a failed rung and uses the CPU.
**For whoever packages it.** A notarised app runs with the hardened runtime, whose library
validation refuses to `dlopen` a library signed by another team. A bundled
`Contents/Frameworks/libonnxruntime.dylib` must be signed with the app. A runtime the user
fetched needs the `com.apple.security.cs.disable-library-validation` entitlement, or it will not
load, and the app will be the tract build without saying why beyond one log line.
## 3. The diagnostic build
Every macOS build is in the hands of someone who can send a log but cannot attach a debugger,
so it is set up to log like a debug build while running at release speed.
- **The log says more.** With no `RUST_LOG`, the desktop's default filter is `debug` for every
`dr_*` crate, for `darkroom_desktop`, and for `onnxruntime`. That last one is ONNX Runtime's
own session log, which the engine forwards into `log` on every platform (`session.rs`,
`with_runtime_log`). At `debug` it includes how many nodes each provider took. At `trace`
(`RUST_LOG=onnxruntime=trace`) it lists every node's placement, which is long. The log cap is
the same as everywhere (two files of 4 MiB).
- **Backtraces have line numbers.** `--profile diagnostic` is release plus line tables. On
macOS the tables go into a `.dSYM` beside the executable, and the backtrace in a crash record
finds them only if the `.dSYM` stays next to the binary. Keep it in the bundle.
## 4. What to ask a Mac user for
`~/Library/Logs/darkroom/darkroom.log`, plus `darkroom.log.1` if present, after the first launch
and after the first scan with faces. Console.app lists it under *Log Reports*. The Settings
diagnostics bundle collects the same files. The lines that answer the open questions are:
| Line | What it tells us |
|---|---|
| `inference: ONNX Runtime … from …` / `inference: runtime tract` | Whether a runtime was found, and which one |
| `inference: floor … ms on the CPU provider` | The CPU number for §2's table |
| `inference: CoreML session built in … s` | CoreML's first compile of the probe model |
| `inference: CoreML rejected: …` / `failed: …` | Why the CPU was kept |
| `onnxruntime` lines naming `CoreMLExecutionProvider::GetCapability` | How much of the graph CoreML took |
| `inference: the app died during …` | The crash guard fired, and on what |
| `inference: compiling … for CoreML` / `ready on CoreML in … s` | Each model's compile, and any that CoreML refused |
Also ask for the settings row (*Settings › About › Inference*), which is one line and says the
same in short. When one of these logs comes back with CoreML numbers, they go into
[inference.md §1–2](inference.md), and footnote ⁵ becomes a measurement.