While building an app with large language model inferencing on device, I got gibberish output. After carefully examining every detail, I found it's caused by the fused scaledDotProductAttention operation. I switched back to the discrete operations and problem solved. To reproduce the bug, please check https://github.com/zhoudan111/MPSGraph_SDPA_bug

As TN3135 clearly explains the limitations apple puts on the low level networking, it doesn’t really give a reason. Presumably the power consumption problem. But as the battery technology continues evolving, it could be exciting that apple might loose the restrictions someday. The watch itself is powerful enough to do a lot of sophisticated works, sure it works best with companion apps on iPhone, but even as a standalone device, we can still provide many advanced user experience with low level networking supports. wish apple guys can read it and give a consideration.

I'm implementing an LLM with Metal Performance Shader Graph, but encountered a very strange behavior, occasionally, the model will report an error message as this: LLVM ERROR: SmallVector unable to grow. Requested capacity (9223372036854775808) is larger than maximum value for size type (4294967295) and crash, the stack backtrace screenshot is attached. Note that 5th frame is mlir::getIntValues<long long> and 6th frame is llvm::SmallVectorBase<unsigned int>::grow_pod It looks like mlir mistakenly took a 64 bit value for a 32 bit type. Unfortunately, I could not found the source code of mlir::getIntValues, maybe it's Apple's closed source fork of llvm for MPS implementation? Anyway, any opinion or suggestion on that?