[Bug] 推DeepCoder-14B中间报错

[cyber-tao]

Checklist

• [x] 1. I have searched related issues but cannot get the expected help.
• [x] 2. The bug has not been fixed in the latest version.
• [x] 3. Please note that if the bug-related issue you submitted lacks corresponding environment info and a minimal reproducible demo, it will be challenging for us to reproduce and resolve the issue, reducing the likelihood of receiving feedback.

Describe the bug

推DeepCoder-14B时报错，但任务又在继续，没有中断，不知道对结果有什么影响。

Reproduction

lmdeploy serve api_server DeepCoder-14B-Preview/ --model-name DeepCoder-14B --tp 4 --chat-template deepseek-r1 --log-level INFO

Environment

sys.platform: linux
Python: 3.12.3 (main, Feb  4 2025, 14:48:35) [GCC 13.3.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0,1,2,3: NVIDIA GeForce RTX 3090
CUDA_HOME: /usr
NVCC: Cuda compilation tools, release 12.0, V12.0.140
GCC: x86_64-linux-gnu-gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
PyTorch: 2.4.1+cu121
PyTorch compiling details: PyTorch built with:
  - GCC 9.3
  - C++ Version: 201703
  - Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v3.4.2 (Git Hash 1137e04ec0b5251ca2b4400a4fd3c667ce843d67)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - LAPACK is enabled (usually provided by MKL)
  - NNPACK is enabled
  - CPU capability usage: AVX512
  - CUDA Runtime 12.1
  - NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90
  - CuDNN 90.1  (built against CUDA 12.4)
  - Magma 2.6.1
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=12.1, CUDNN_VERSION=9.1.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=2.4.1, USE_CUDA=ON, USE_CUDNN=ON, USE_CUSPARSELT=1, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, 

TorchVision: 0.19.1+cu121
LMDeploy: 0.7.2.post1+
transformers: 4.51.0.dev0
gradio: Not Found
fastapi: 0.115.6
pydantic: 2.10.4
triton: 3.0.0
NVIDIA Topology: 
	[4mGPU0	GPU1	GPU2	GPU3	CPU Affinity	NUMA Affinity	GPU NUMA ID[0m
GPU0	 X 	NODE	SYS	NV4	0-11,24-35	0		N/A
GPU1	NODE	 X 	NV4	SYS	0-11,24-35	0		N/A
GPU2	SYS	NV4	 X 	NODE	12-23,36-47	1		N/A
GPU3	NV4	SYS	NODE	 X 	12-23,36-47	1		N/A

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

Error traceback

2025-04-14 14:29:20,646 - lmdeploy - INFO - turbomind.py:598 - [async_stream_infer] CancelledError                                                                                   [0/1838]2025-04-14 14:29:20,646 - lmdeploy - ERROR - async_engine.py:592 - [safe_run] exception caught: CancelledError Cancelled by cancel scope 7c943c1f9820                                        
[TM][INFO] [Interrupt] slot 0, request 2, stop 1, end 0                                  
Exception in callback StreamingSemaphore.release()                                       
handle: <Handle StreamingSemaphore.release()>                                                 
Traceback (most recent call last):                                                            
  File "/usr/lib/python3.12/asyncio/events.py", line 88, in _run           
    self._context.run(self._callback, *self._args)                         
  File "/workdir/pyenvs/lmdeploy/lib/python3.12/site-packages/lmdeploy/turbomind/turbomind.py", line 382, in release                                                                         
    self.fut.set_result(None)
asyncio.exceptions.InvalidStateError: invalid state