`docker/macos` builds for aarch64-apple-darwin from Linux with
cargo-zigbuild. Zig carries libSystem and the C headers, so tract's SIMD
kernels compile and the engine's test binaries and examples link as Mach-O
arm64 — the check `cargo check --target` could not do, because tract's
build script needs a macOS C compiler. Crates that link an Apple framework
(dr-plat's keyring, and so the app) still need the Xcode SDK and fail at
the link; macos.md says so.
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.
dtourolle