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.
Lowered with eager attention and rank-3 attention (the singleton batch folded
into the head dim), mean pooling written with keepdim so the reduction stays on
the GPU, and the token embedding kept off texture storage, without which fp16
returns silently wrong values (pytorch/executorch#22333).
Verified against the CPU reference at cosine >= 0.99997 on an Adreno 840 and a
Mali-G76.
Requires the ExecuTorch 1.4.1 Vulkan runtime from the v0.10.0-libs-1.4.1
artifacts.
