[Bug]: Unable to deploy Qwen2.5-VL-3B-Instruct after updating vLLM to latest version #16791
Description
Your current environment
The output of `python collect_env.py`
INFO 04-17 15:28:34 [__init__.py:239] Automatically detected platform cuda. Collecting environment information... PyTorch version: 2.6.0+cu124 Is debug build: False CUDA used to build PyTorch: 12.4 ROCM used to build PyTorch: N/AOS: Ubuntu 24.04.1 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version: Could not collect
CMake version: version 3.28.3
Libc version: glibc-2.39
Python version: 3.12.7 | packaged by Anaconda, Inc. | (main, Oct 4 2024, 13:27:36) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.8.0-57-generic-x86_64-with-glibc2.39
Is CUDA available: True
CUDA runtime version: 12.6.85
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA H20
GPU 1: NVIDIA H20
GPU 2: NVIDIA H20
GPU 3: NVIDIA H20
GPU 4: NVIDIA H20
GPU 5: NVIDIA H20
GPU 6: NVIDIA H20
GPU 7: NVIDIA H20
Nvidia driver version: 565.57.01
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 160
On-line CPU(s) list: 0-159
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Platinum 8460Y+
CPU family: 6
Model: 143
Thread(s) per core: 2
Core(s) per socket: 40
Socket(s): 2
Stepping: 8
CPU(s) scaling MHz: 43%
CPU max MHz: 3700.0000
CPU min MHz: 800.0000
BogoMIPS: 4000.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hfi vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 3.8 MiB (80 instances)
L1i cache: 2.5 MiB (80 instances)
L2 cache: 160 MiB (80 instances)
L3 cache: 210 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110,112,114,116,118,120,122,124,126,128,130,132,134,136,138,140,142,144,146,148,150,152,154,156,158
NUMA node1 CPU(s): 1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79,81,83,85,87,89,91,93,95,97,99,101,103,105,107,109,111,113,115,117,119,121,123,125,127,129,131,133,135,137,139,141,143,145,147,149,151,153,155,157,159
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] numpy==2.2.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-cusparselt-cu12==0.6.2
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pyzmq==26.4.0
[pip3] torch==2.6.0
[pip3] torchaudio==2.6.0
[pip3] torchvision==0.21.0
[pip3] transformers==4.51.3
[pip3] triton==3.2.0
[conda] _anaconda_depends 2024.10 py312_mkl_0
[conda] blas 1.0 mkl
[conda] mkl 2023.1.0 h213fc3f_46344
[conda] mkl-service 2.4.0 py312h5eee18b_1
[conda] mkl_fft 1.3.10 py312h5eee18b_0
[conda] mkl_random 1.2.7 py312h526ad5a_0
[conda] numpy 1.26.4 py312hc5e2394_0
[conda] numpy-base 1.26.4 py312h0da6c21_0
[conda] numpydoc 1.7.0 py312h06a4308_0
[conda] nvidia-cublas-cu12 12.4.5.8 pypi_0 pypi
[conda] nvidia-cuda-cupti-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cuda-nvrtc-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cuda-runtime-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cudnn-cu12 9.1.0.70 pypi_0 pypi
[conda] nvidia-cufft-cu12 11.2.1.3 pypi_0 pypi
[conda] nvidia-curand-cu12 10.3.5.147 pypi_0 pypi
[conda] nvidia-cusolver-cu12 11.6.1.9 pypi_0 pypi
[conda] nvidia-cusparse-cu12 12.3.1.170 pypi_0 pypi
[conda] nvidia-cusparselt-cu12 0.6.2 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.21.5 pypi_0 pypi
[conda] nvidia-nvjitlink-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-nvtx-cu12 12.4.127 pypi_0 pypi
[conda] pyzmq 25.1.2 py312h6a678d5_0
[conda] torch 2.6.0 pypi_0 pypi
[conda] transformers 4.51.0 pypi_0 pypi
[conda] triton 3.2.0 pypi_0 pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.8.4
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 NIC1 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X NV18 NV18 NV18 NV18 NV18 NV18 NV18 SYS SYS 0,2,4,6,8,10 0 N/A
GPU1 NV18 X NV18 NV18 NV18 NV18 NV18 NV18 SYS SYS 0,2,4,6,8,10 0 N/A
GPU2 NV18 NV18 X NV18 NV18 NV18 NV18 NV18 SYS SYS 0,2,4,6,8,10 0 N/A
GPU3 NV18 NV18 NV18 X NV18 NV18 NV18 NV18 SYS SYS 0,2,4,6,8,10 0 N/A
GPU4 NV18 NV18 NV18 NV18 X NV18 NV18 NV18 NODE NODE 1,3,5,7,9,11 1 N/A
GPU5 NV18 NV18 NV18 NV18 NV18 X NV18 NV18 PIX NODE 1,3,5,7,9,11 1 N/A
GPU6 NV18 NV18 NV18 NV18 NV18 NV18 X NV18 NODE NODE 1,3,5,7,9,11 1 N/A
GPU7 NV18 NV18 NV18 NV18 NV18 NV18 NV18 X NODE PIX 1,3,5,7,9,11 1 N/A
NIC0 SYS SYS SYS SYS NODE PIX NODE NODE X NODE
NIC1 SYS SYS SYS SYS NODE NODE NODE PIX NODE X
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
NIC Legend:
NIC0: mlx5_0
NIC1: mlx5_1
CUDA_VISIBLE_DEVICES=6
CUDA_VISIBLE_DEVICES=6
LD_LIBRARY_PATH=/usr/local/cuda/lib64:
VLLM_USE_V1=0
NCCL_CUMEM_ENABLE=0
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY
🐛 Describe the bug
After updating to the latest version of vLLM, I'm encountering issues when trying to deploy the qwen2.5-instruct model. The deployment process hangs indefinitely, and when terminated with Ctrl+C, the following error is displayed:
vllm serve Qwen/Qwen2.5-VL-3B-Instruct --port 12345
INFO 04-17 15:26:31 [init.py:239] Automatically detected platform cuda.
INFO 04-17 15:26:33 [api_server.py:1034] vLLM API server version 0.8.4
INFO 04-17 15:26:33 [api_server.py:1035] args: Namespace(subparser='serve', model_tag='Qwen/Qwen2.5-VL-3B-Instruct', config='', host=None, port=12345, uvicorn_log_level='info', disable_uvicorn_access_log=False, allow_credentials=False, allowed_origins=[''], allowed_methods=[''], allowed_headers=[''], api_key=None, lora_modules=None, prompt_adapters=None, chat_template=None, chat_template_content_format='auto', response_role='assistant', ssl_keyfile=None, ssl_certfile=None, ssl_ca_certs=None, enable_ssl_refresh=False, ssl_cert_reqs=0, root_path=None, middleware=[], return_tokens_as_token_ids=False, disable_frontend_multiprocessing=False, enable_request_id_headers=False, enable_auto_tool_choice=False, tool_call_parser=None, tool_parser_plugin='', model='Qwen/Qwen2.5-VL-3B-Instruct', task='auto', tokenizer=None, hf_config_path=None, skip_tokenizer_init=False, revision=None, code_revision=None, tokenizer_revision=None, tokenizer_mode='auto', trust_remote_code=False, allowed_local_media_path=None, load_format='auto', download_dir=None, model_loader_extra_config=None, use_tqdm_on_load=True, config_format=<ConfigFormat.AUTO: 'auto'>, dtype='auto', kv_cache_dtype='auto', max_model_len=None, guided_decoding_backend='xgrammar', logits_processor_pattern=None, model_impl='auto', distributed_executor_backend=None, pipeline_parallel_size=1, tensor_parallel_size=1, data_parallel_size=1, enable_expert_parallel=False, max_parallel_loading_workers=None, ray_workers_use_nsight=False, disable_custom_all_reduce=False, block_size=None, enable_prefix_caching=None, prefix_caching_hash_algo='builtin', disable_sliding_window=False, use_v2_block_manager=True, num_lookahead_slots=0, seed=None, swap_space=4, cpu_offload_gb=0, gpu_memory_utilization=0.9, num_gpu_blocks_override=None, max_num_batched_tokens=None, max_num_partial_prefills=1, max_long_partial_prefills=1, long_prefill_token_threshold=0, max_num_seqs=None, max_logprobs=20, disable_log_stats=False, quantization=None, rope_scaling=None, rope_theta=None, hf_token=None, hf_overrides=None, enforce_eager=False, max_seq_len_to_capture=8192, tokenizer_pool_size=0, tokenizer_pool_type='ray', tokenizer_pool_extra_config=None, limit_mm_per_prompt=None, mm_processor_kwargs=None, disable_mm_preprocessor_cache=False, enable_lora=False, enable_lora_bias=False, max_loras=1, max_lora_rank=16, lora_extra_vocab_size=256, lora_dtype='auto', long_lora_scaling_factors=None, max_cpu_loras=None, fully_sharded_loras=False, enable_prompt_adapter=False, max_prompt_adapters=1, max_prompt_adapter_token=0, device='auto', num_scheduler_steps=1, multi_step_stream_outputs=True, scheduler_delay_factor=0.0, enable_chunked_prefill=None, speculative_config=None, ignore_patterns=[], preemption_mode=None, served_model_name=None, qlora_adapter_name_or_path=None, show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, disable_async_output_proc=False, scheduling_policy='fcfs', scheduler_cls='vllm.core.scheduler.Scheduler', override_neuron_config=None, override_pooler_config=None, compilation_config=None, kv_transfer_config=None, worker_cls='auto', worker_extension_cls='', generation_config='auto', override_generation_config=None, enable_sleep_mode=False, calculate_kv_scales=False, additional_config=None, enable_reasoning=False, reasoning_parser=None, disable_cascade_attn=False, disable_chunked_mm_input=False, disable_log_requests=False, max_log_len=None, disable_fastapi_docs=False, enable_prompt_tokens_details=False, enable_server_load_tracking=False, dispatch_function=<function ServeSubcommand.cmd at 0x7dac146eb420>)
INFO 04-17 15:26:40 [config.py:689] This model supports multiple tasks: {'classify', 'embed', 'score', 'reward', 'generate'}. Defaulting to 'generate'.
WARNING 04-17 15:26:40 [arg_utils.py:1603] The model has a long context length (128000). This may causeOOM during the initial memory profiling phase, or result in low performance due to small KV cache size. Consider setting --max-model-len to a smaller value.
INFO 04-17 15:26:40 [api_server.py:246] Started engine process with PID 2279045
INFO 04-17 15:26:43 [init.py:239] Automatically detected platform cuda.
INFO 04-17 15:26:45 [llm_engine.py:243] Initializing a V0 LLM engine (v0.8.4) with config: model='Qwen/Qwen2.5-VL-3B-Instruct', speculative_config=None, tokenizer='Qwen/Qwen2.5-VL-3B-Instruct', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=128000, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='xgrammar', reasoning_backend=None), observability_config=ObservabilityConfig(show_hidden_metrics=False, otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=None, served_model_name=Qwen/Qwen2.5-VL-3B-Instruct, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=None, chunked_prefill_enabled=False, use_async_output_proc=True, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=None, compilation_config={"splitting_ops":[],"compile_sizes":[],"cudagraph_capture_sizes":[256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],"max_capture_size":256}, use_cached_outputs=True,
INFO 04-17 15:26:47 [cuda.py:292] Using Flash Attention backend.
INFO 04-17 15:26:48 [parallel_state.py:959] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, TP rank 0
INFO 04-17 15:26:48 [model_runner.py:1110] Starting to load model Qwen/Qwen2.5-VL-3B-Instruct...
WARNING 04-17 15:26:48 [vision.py:93] Current vllm-flash-attn has a bug inside vision module, so we use xformers backend instead. You can run pip install flash-attn to use flash-attention backend.
INFO 04-17 15:26:48 [config.py:3466] cudagraph sizes specified by model runner [1, 2, 4, 8, 16, 24, 32, 40, 48, 56, 64, 72, 80, 88, 96, 104, 112, 120, 128, 136, 144, 152, 160, 168, 176, 184, 192, 200, 208, 216, 224, 232, 240, 248, 256] is overridden by config [256, 128, 2, 1, 4, 136, 8, 144, 16, 152, 24, 160, 32, 168, 40, 176, 48, 184, 56, 192, 64, 200, 72, 208, 80, 216, 88, 120, 224, 96, 232, 104, 240, 112, 248]
INFO 04-17 15:26:49 [weight_utils.py:265] Using model weights format ['.safetensors']
Loading safetensors checkpoint shards: 0% Completed | 0/2 [00:00<?, ?it/s]
Loading safetensors checkpoint shards: 50% Completed | 1/2 [00:00<00:00, 1.27it/s]
Loading safetensors checkpoint shards: 100% Completed | 2/2 [00:01<00:00, 1.12it/s]
Loading safetensors checkpoint shards: 100% Completed | 2/2 [00:01<00:00, 1.14it/s]
INFO 04-17 15:26:51 [loader.py:458] Loading weights took 1.85 seconds
INFO 04-17 15:26:51 [model_runner.py:1146] Model loading took 7.1557 GiB and 3.171301 seconds
Using a slow image processor as use_fast is unset and a slow processor was saved with this model. use_fast=True will be the default behavior in v4.52, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with use_fast=False.
^C^CTraceback (most recent call last):
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 264, in build_async_engine_client_from_engine_args
await mq_engine_client.setup()
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/vllm/engine/multiprocessing/client.py", line 284, in setup
response = await self._wait_for_server_rpc(socket)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/vllm/engine/multiprocessing/client.py", line 392, in _wait_for_server_rpc
return await self._send_get_data_rpc_request(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/vllm/engine/multiprocessing/client.py", line 320, in _send_get_data_rpc_request
if await socket.poll(timeout=VLLM_RPC_TIMEOUT) == 0:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
asyncio.exceptions.CancelledError
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/zhiyuan/myenv/bin/vllm", line 10, in
sys.exit(main())
^^^^^^
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/vllm/entrypoints/cli/main.py", line 51, in main
args.dispatch_function(args)
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/vllm/entrypoints/cli/serve.py", line 27, in cmd
uvloop.run(run_server(args))
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/uvloop/init.py", line 109, in run
return __asyncio.run(
^^^^^^^^^^^^^^
File "/home/zhiyuan/anaconda3/lib/python3.12/asyncio/runners.py", line 194, in run
return runner.run(main)
^^^^^^^^^^^^^^^^
File "/home/zhiyuan/anaconda3/lib/python3.12/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "uvloop/loop.pyx", line 1512, in uvloop.loop.Loop.run_until_complete
File "uvloop/loop.pyx", line 1505, in uvloop.loop.Loop.run_until_complete
File "uvloop/loop.pyx", line 1379, in uvloop.loop.Loop.run_forever
File "uvloop/loop.pyx", line 557, in uvloop.loop.Loop._run
File "uvloop/loop.pyx", line 476, in uvloop.loop.Loop._on_idle
File "uvloop/cbhandles.pyx", line 83, in uvloop.loop.Handle._run
File "uvloop/cbhandles.pyx", line 63, in uvloop.loop.Handle._run
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/uvloop/init.py", line 61, in wrapper
return await main
^^^^^^^^^^
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 1069, in run_server
async with build_async_engine_client(args) as engine_client:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/zhiyuan/anaconda3/lib/python3.12/contextlib.py", line 210, in aenter
return await anext(self.gen)
^^^^^^^^^^^^^^^^^^^^^
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 146, in build_async_engine_client
async with build_async_engine_client_from_engine_args(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/zhiyuan/anaconda3/lib/python3.12/contextlib.py", line 210, in aenter
return await anext(self.gen)
^^^^^^^^^^^^^^^^^^^^^
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 291, in build_async_engine_client_from_engine_args
from prometheus_client import multiprocess
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/prometheus_client/init.py", line 3, in
from . import (
File "/home/zhiyuan/myenv/lib/python3.12/site-packages/prometheus_client/metrics.py", line 12, in
from .context_managers import ExceptionCounter, InprogressTracker, Timer
File "", line 1360, in _find_and_load
File "", line 1331, in _find_and_load_unlocked
File "", line 935, in _load_unlocked
File "", line 991, in exec_module
File "", line 1124, in get_code
File "", line 753, in _compile_bytecode
File "/home/zhiyuan/anaconda3/lib/python3.12/asyncio/runners.py", line 157, in _on_sigint
raise KeyboardInterrupt()
KeyboardInterrupt
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