lm-sys / lm-sys/FastChat

tiiuae/falcon-7b does not work on Apple M1 GPU (MPS)

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Python
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Description

Hey,

I am trying to run

python3 -m fastchat.serve.cli --model-path tiiuae/falcon-7b --device mps
tiiuae/falcon-7b

Prompt:
User: Who is King Charles?

This leads to the following error:

Assistant: /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/transformers/generation/utils.py:723: UserWarning: MPS: no support for int64 repeats mask, casting it to int32 (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/mps/operations/Repeat.mm:236.)
  input_ids = input_ids.repeat_interleave(expand_size, dim=0)
loc("varianceEps"("(mpsFileLoc): /AppleInternal/Library/BuildRoots/c2cb9645-dafc-11ed-aa26-6ec1e3b3f7b3/Library/Caches/com.apple.xbs/Sources/MetalPerformanceShadersGraph/mpsgraph/MetalPerformanceShadersGraph/Core/Files/MPSGraphUtilities.mm":228:0)): error: input types 'tensor<1x12x1xf16>' and 'tensor<1xf32>' are not broadcast compatible
LLVM ERROR: Failed to infer result type(s).
[1]    64954 abort      python3 -m fastchat.serve.cli --model-path tiiuae/falcon-7b --device mps
/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/multiprocessing/resource_tracker.py:224: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
  warnings.warn('resource_tracker: There appear to be %d '

Is there anything I am missing?
Thanks!

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First steps

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  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reproducing the reported python3 -m fastchat.serve.cli command with tiiuae/falcon-7b and --device mps. Investigate the reported MPS type error involving varianceEps, then verify that the model can run on Apple M1 GPU without the reported abort.

Written by the indexing model from the issue text.

Assessment

Tech stack
huggingface, python, pytorch
Domain
backend, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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