Offline.py LLMEngine.__init__() missing 1 required positional argument: 'simulator_config'

[fivebamboo694]

I completed the installation of DistServe. When I tried to run the offline.py using my downloaded llama2 model, I encountered the following problem.

Traceback (most recent call last): File "/home/wangzhusheng/DistServe/./distserve/examples/offline.py", line 31, in llm = OfflineLLM( File "/home/wangzhusheng/DistServe/distserve/llm.py", line 42, in init self.engine = LLMEngine( TypeError: LLMEngine.init() missing 1 required positional argument: 'simulator_config'

So, I read the source code and find that there are 5 parameters in OfflineLLM class but 6 parameters in LLMEngine class, simulator_config is missing now. Could you please fix this issue in the provided examples?

[PKUFlyingPig]

Have you pulled the updated main branch? This bug has already been fixed in PR #11.

[fivebamboo694]

Have you pulled the updated main branch? This bug has already been fixed in PR #11.

Thanks. This problem is fixed. However, when I try to run the command python ./examples/offline.py --model llama2-7B using my downloaded llama2-7B model, I encounter the following problem:

ray.exceptions.RayTaskError(RuntimeError): ray::ParaWorker.init_model() (pid=483561, ip=61.12.226.94, actor_id=2e36020ed4c51a284247d02201000000, repr=<distserve.worker.ParaWorker object at 0x7fca76f9a3e0>) File "/home/wangzhusheng/DistServe/distserve/worker.py", line 97, in init_model self.model.load_weight(path) RuntimeError

INFO 12:56:58 Starting LLMEngine's event loops INFO 12:56:58 (context) Forwarding with lengths [17, 6, 6, 8] INFO 12:56:58 (context) 1 waiting, 0 finished but unaccepted, 5 blocks occupied by on-the-fly requests INFO 12:56:58 (decoding) CPU blocks: 0 / 128 (0.00%) used, (0 swapping in) INFO 12:56:58 (decoding) GPU blocks: 0 / 2044 (0.00%) used, (0 swapping out) INFO 12:56:58 (decoding) 0 unaccepted, 0 waiting, 0 processing

When I use ctrl+c to quit, the following content is printed，

Gpt::load() - llama2-7B/decoder.embed_tokens.weight.pt not found Task exception was never retrieved future: <Task finished name='Task-19' coro=<LLMEngine.start_all_event_loops() done, defined at /home/wangzhusheng/DistServe/distserve/engine.py:244> exception=RayTaskError(RuntimeError)(RuntimeError('Please load the weight before inference.'))> Traceback (most recent call last): File "/home/wangzhusheng/DistServe/distserve/engine.py", line 251, in start_all_event_loops await asyncio.gather( File "/home/wangzhusheng/DistServe/distserve/single_stage_engine.py", line 423, in start_event_loop await asyncio.gather(event_loop1(), event_loop2()) File "/home/wangzhusheng/DistServe/distserve/single_stage_engine.py", line 415, in event_loop1 await self._step() File "/home/wangzhusheng/DistServe/distserve/single_stage_engine.py", line 355, in _step generated_tokens_ids = await self.batches_ret_futures[0] ray.exceptions.RayTaskError(RuntimeError): ray::ParaWorker.step() (pid=483560, ip=61.12.226.94, actor_id=c68576230073ff4124b2037301000000, repr=<distserve.worker.ParaWorker object at 0x7fdcb850a470>) File "/home/wangzhusheng/DistServe/distserve/worker.py", line 217, in step generated_tokens_ids = self.model.forward( RuntimeError: Please load the weight before inference.

Is there any idea to solve this problem? Let me know if I need to provide any further information. Thank you very much!

[PKUFlyingPig]

Can you run ./examples/offline.py directly? The script will automatically download the model meta-llama/Llama-2-7b-hf from huggingface and do the weight conversion.

[fivebamboo694]

Can you run ./examples/offline.py directly? The script will automatically download the model meta-llama/Llama-2-7b-hf from huggingface and do the weight conversion.

No, I am not able to run ./examples/offline.py directly because of some network connection problem. So, I try to use the downloaded model for simplicity.

[Chasingdreams6]

I got the same problem when I try to run local Llama7b chat model.

(ParaWorker pid=59714) Gpt<T>::load() - /huggingface/hub/Llama-2-7b-hf/decoder.embed_tokens.weight.pt not found
Task exception was never retrieved
future: <Task finished name='Task-7' coro=<_wrap_awaitable() done, defined at /root/micromamba/envs/distserve/lib/python3.10/asyncio/tasks.py:643> exception=RayTaskError(RuntimeError)(RuntimeError(''))>
Traceback (most recent call last):
  File "/root/micromamba/envs/distserve/lib/python3.10/asyncio/tasks.py", line 650, in _wrap_awaitable
    return (yield from awaitable.__await__())
ray.exceptions.RayTaskError(RuntimeError): ray::ParaWorker.init_model() (pid=59713, ip=10.140.0.192, actor_id=cb94185f1857e5d5564fb66d01000000, repr=<distserve.worker.ParaWorker object at 0x7f75402f2ef0>)
  File "/app/distserve/distserve/worker.py", line 98, in init_model
    self.model.load_weight(path)
RuntimeError

It seems like my local 'decoder.embed_tokens.weight.pt' is missing, is the file offered by LLama, or generated by distServe?