quantized duplicated precisions.json, which is authoritative for the
quantized/non-quantized partition. default expressed a per-repository
recommendation nothing consumed: the library resolves its own per-platform
default. Both are gone from the schema.
perf(coreml): run decode on the CPU, not the Neural Engine
decode is a single-token program whose cost on device is dispatch rather than arithmetic, so it was paying Neural Engine overhead on every call under ExecuTorch's ALL default. Pinning only decode to CPU_ONLY (encode stays on ALL) measures 6.7 ms/step against 20.0 on an iPhone 16.
On 14.5s of real speech the whole transcribe is 1.5-3.1x faster depending on size, with a byte-identical transcript: this removes overhead, it does not change numerics.
Exported from export-scripts MR !18, built on main pins (ExecuTorch 1.4.1). Replaces an ExecuTorch 1.2.0 build of the same change; transcripts verified byte-identical on device at all six sizes.
perf(coreml): run decode on the CPU, not the Neural Engine
decode is a single-token program whose cost on device is dispatch rather than arithmetic, so it was paying Neural Engine overhead on every call under ExecuTorch's ALL default. Pinning only decode to CPU_ONLY (encode stays on ALL) measures 6.7 ms/step against 20.0 on an iPhone 16.
On 14.5s of real speech the whole transcribe is 1.5-3.1x faster depending on size, with a byte-identical transcript: this removes overhead, it does not change numerics.
Exported from export-scripts MR !18.
