[Bug]: crash during debug, works ok running cli #16006
Description
Your current environment
The output of `python collect_env.py`
Collecting environment information...
PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A
OS: Ubuntu 22.04.5 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.31.4
Libc version: glibc-2.35
Python version: 3.12.9 (main, Feb 5 2025, 08:49:00) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.8.0-50-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.1.105
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4090
Nvidia driver version: 570.86.15
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: 39 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 12
On-line CPU(s) list: 0-11
Vendor ID: GenuineIntel
Model name: Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz
CPU family: 6
Model: 158
Thread(s) per core: 2
Core(s) per socket: 6
Socket(s): 1
Stepping: 10
CPU max MHz: 4600.0000
CPU min MHz: 800.0000
BogoMIPS: 6399.96
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 pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb pti ssbd ibrs ibpb stibp tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp vnmi md_clear flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 192 KiB (6 instances)
L1i cache: 192 KiB (6 instances)
L2 cache: 1.5 MiB (6 instances)
L3 cache: 12 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-11
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled
Vulnerability L1tf: Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable
Vulnerability Mds: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Meltdown: Mitigation; PTI
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Mitigation; IBRS
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; IBRS; IBPB conditional; STIBP conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds: Mitigation; Microcode
Vulnerability Tsx async abort: Mitigation; TSX disabled
Versions of relevant libraries:
[pip3] numpy==1.26.4
[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-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pyzmq==26.2.1
[pip3] torch==2.5.1
[pip3] torchaudio==2.5.1
[pip3] torchvision==0.20.1
[pip3] transformers==4.48.3
[pip3] triton==3.1.0
[conda] blas 1.0 mkl
[conda] cuda-cudart 11.7.99 0 nvidia
[conda] cuda-cupti 11.7.101 0 nvidia
[conda] cuda-libraries 11.7.1 0 nvidia
[conda] cuda-nvrtc 11.7.99 0 nvidia
[conda] cuda-nvtx 11.7.91 0 nvidia
[conda] cuda-runtime 11.7.1 0 nvidia
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] libcublas 11.10.3.66 0 nvidia
[conda] libcufft 10.7.2.124 h4fbf590_0 nvidia
[conda] libcufile 1.8.0.34 0 nvidia
[conda] libcurand 10.3.4.52 0 nvidia
[conda] libcusolver 11.4.0.1 0 nvidia
[conda] libcusparse 11.7.4.91 0 nvidia
[conda] libjpeg-turbo 2.0.0 h9bf148f_0 pytorch
[conda] libnpp 11.7.4.75 0 nvidia
[conda] libnvjpeg 11.8.0.2 0 nvidia
[conda] mkl 2023.1.0 h213fc3f_46344
[conda] mkl-service 2.4.0 py311h5eee18b_1
[conda] mkl_fft 1.3.8 py311h5eee18b_0
[conda] mkl_random 1.2.4 py311hdb19cb5_0
[conda] numpy 1.26.0 py311h08b1b3b_0
[conda] numpy-base 1.26.0 py311hf175353_0
[conda] pytorch 2.1.0 py3.11_cpu_0 pytorch
[conda] pytorch-cuda 11.7 h778d358_5 pytorch
[conda] pytorch-mutex 1.0 cpu pytorch
[conda] torchaudio 2.1.0 py311_cpu pytorch
[conda] torchvision 0.16.0 py311_cpu pytorch
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.7.3.dev62+gcb080f32.d20250213
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X 0-11 0 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
LD_LIBRARY_PATH=:/home/cju/.mujoco/mujoco210/bin:/usr/lib/nvidia
CUDA_HOME=/usr/local/cuda
CUDA_HOME=/usr/local/cuda
VLLM_USE_V1=1
NCCL_CUMEM_ENABLE=0
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY
🐛 Describe the bug
running the cli vllm serve facebook/opt-125m works out ok. The server starts up.
however, it crashes when debugging it in vscode with the following launch.json:
{
// Use IntelliSense to learn about possible attributes.
// Hover to view descriptions of existing attributes.
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
"version": "0.2.0",
"configurations": [
{
"name": "vllm serve",
"type": "debugpy",
"request": "launch",
"program": "${workspaceFolder}/vllm/scripts.py",
"console": "integratedTerminal",
"justMyCode": false,
"args": [
"serve", "facebook/opt-125m"
]
}
]
}
The error is:
INFO 04-03 17:56:20 weight_utils.py:254] Using model weights format ['*.safetensors']
INFO 04-03 17:56:21 weight_utils.py:306] No model.safetensors.index.json found in remote.
Loading safetensors checkpoint shards: 0% Completed | 0/1 [00:00<?, ?it/s]
Loading safetensors checkpoint shards: 100% Completed | 1/1 [00:06<00:00, 6.66s/it]
Loading safetensors checkpoint shards: 100% Completed | 1/1 [00:06<00:00, 6.66s/it]INFO 04-03 17:56:28 gpu_model_runner.py:918] Loading model weights took 2.8875 GB
INFO 04-03 17:57:17 backends.py:408] Using cache directory: /home/cju/.cache/vllm/torch_compile_cache/ca60c2a0fd/rank_0 for vLLM's torch.compile
INFO 04-03 17:57:17 backends.py:418] Dynamo bytecode transform time: 26.71 s
INFO 04-03 17:57:19 backends.py:115] Directly load the compiled graph for shape None from the cache
ERROR 04-03 17:57:33 core.py:208] EngineCore hit an exception: Traceback (most recent call last):
ERROR 04-03 17:57:33 core.py:208] File "_pydevd_sys_monitoring\_pydevd_sys_monitoring_cython.pyx", line 499, in _pydevd_sys_monitoring_cython._get_code_line_info
ERROR 04-03 17:57:33 core.py:208] KeyError: <code object forward at 0x4d452b40, file "/home/cju/aigc/vllm/vllm/model_executor/models/qwen2.py", line 327>
ERROR 04-03 17:57:33 core.py:208]
ERROR 04-03 17:57:33 core.py:208] During handling of the above exception, another exception occurred:
ERROR 04-03 17:57:33 core.py:208]
ERROR 04-03 17:57:33 core.py:208] Traceback (most recent call last):
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/v1/engine/core.py", line 200, in run_engine_core
ERROR 04-03 17:57:33 core.py:208] engine_core = EngineCoreProc(*args, **kwargs)
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/v1/engine/core.py", line 153, in init
ERROR 04-03 17:57:33 core.py:208] super().init(vllm_config, executor_class)
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/v1/engine/core.py", line 51, in init
ERROR 04-03 17:57:33 core.py:208] num_gpu_blocks, num_cpu_blocks = self._initialize_kv_caches(
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/v1/engine/core.py", line 76, in _initialize_kv_caches
ERROR 04-03 17:57:33 core.py:208] availble_gpu_memory = self.model_executor.determine_available_memory()
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/v1/executor/abstract.py", line 60, in determine_available_memory
ERROR 04-03 17:57:33 core.py:208] output = self.collective_rpc("determine_available_memory")
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/executor/uniproc_executor.py", line 51, in collective_rpc
ERROR 04-03 17:57:33 core.py:208] answer = run_method(self.driver_worker, method, args, kwargs)
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/utils.py", line 2220, in run_method
ERROR 04-03 17:57:33 core.py:208] return func(*args, **kwargs)
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/.venv/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
ERROR 04-03 17:57:33 core.py:208] return func(*args, **kwargs)
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/v1/worker/gpu_worker.py", line 163, in determine_available_memory
ERROR 04-03 17:57:33 core.py:208] self.model_runner.profile_run()
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/v1/worker/gpu_model_runner.py", line 1143, in profile_run
ERROR 04-03 17:57:33 core.py:208] hidden_states = self._dummy_run(self.max_num_tokens,
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/.venv/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
ERROR 04-03 17:57:33 core.py:208] return func(*args, **kwargs)
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/v1/worker/gpu_model_runner.py", line 1011, in _dummy_run
ERROR 04-03 17:57:33 core.py:208] hidden_states = model(
ERROR 04-03 17:57:33 core.py:208] ^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/.venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
ERROR 04-03 17:57:33 core.py:208] return self._call_impl(*args, **kwargs)
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/.venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
ERROR 04-03 17:57:33 core.py:208] return forward_call(*args, **kwargs)
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/model_executor/models/qwen2.py", line 486, in forward
ERROR 04-03 17:57:33 core.py:208] hidden_states = self.model(input_ids, positions, kv_caches,
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/compilation/decorators.py", line 238, in call
ERROR 04-03 17:57:33 core.py:208] output = self.compiled_callable(*args, **kwargs)
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/.venv/lib/python3.12/site-packages/torch/_dynamo/eval_frame.py", line 465, in _fn
ERROR 04-03 17:57:33 core.py:208] return fn(*args, **kwargs)
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/vllm/model_executor/models/qwen2.py", line 327, in forward
ERROR 04-03 17:57:33 core.py:208] def forward(
ERROR 04-03 17:57:33 core.py:208]
ERROR 04-03 17:57:33 core.py:208] File "", line 69, in cfunc.to_py.__Pyx_CFunc_893235__29_pydevd_sys_monitoring_cython_object__lParen__etc_to_py_4code_18instruction_offset.wrap
ERROR 04-03 17:57:33 core.py:208] File "_pydevd_sys_monitoring\_pydevd_sys_monitoring_cython.pyx", line 1702, in _pydevd_sys_monitoring_cython._start_method_event
ERROR 04-03 17:57:33 core.py:208] File "_pydevd_sys_monitoring\_pydevd_sys_monitoring_cython.pyx", line 570, in _pydevd_sys_monitoring_cython._get_func_code_info
ERROR 04-03 17:57:33 core.py:208] File "_pydevd_sys_monitoring\_pydevd_sys_monitoring_cython.pyx", line 505, in _pydevd_sys_monitoring_cython._get_code_line_info
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/.venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 1269, in call
ERROR 04-03 17:57:33 core.py:208] return self._torchdynamo_orig_callable(
ERROR 04-03 17:57:33 core.py:208] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/.venv/lib/python3.12/site-packages/torch/_dynamo/convert_frame.py", line 492, in call
ERROR 04-03 17:57:33 core.py:208] unimplemented("generator")
ERROR 04-03 17:57:33 core.py:208] File "/home/cju/aigc/vllm/.venv/lib/python3.12/site-packages/torch/_dynamo/exc.py", line 297, in unimplemented
ERROR 04-03 17:57:33 core.py:208] raise Unsupported(msg, case_name=case_name)
ERROR 04-03 17:57:33 core.py:208] torch._dynamo.exc.Unsupported: generator
ERROR 04-03 17:57:33 core.py:208]
CRITICAL 04-03 17:57:33 core_client.py:156] Got fatal signal from worker processes, shutting down. See stack trace above for root cause issue.
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