[Bug]: Error in V1 engine when run with --convert reward

[iseeyuan]

Your current environment

The output of python collect_env.py

Collecting environment information...
==============================
        System Info
==============================
OS                           : CentOS Stream 9 (x86_64)
GCC version                  : (GCC) 11.5.0 20240719 (Red Hat 11.5.0-11)
Clang version                : Could not collect
CMake version                : version 4.1.0
Libc version                 : glibc-2.34

==============================
       PyTorch Info
==============================
PyTorch version              : 2.8.0+cu129
Is debug build               : False
CUDA used to build PyTorch   : 12.9
ROCM used to build PyTorch   : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.11 (main, Aug 14 2025, 00:00:00) [GCC 11.5.0 20240719 (Red Hat 11.5.0-11)] (64-bit runtime)
Python platform              : Linux-6.4.3-0_fbk15_hardened_2630_gf27365f948db-x86_64-with-glibc2.34

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : 12.9.86
CUDA_MODULE_LOADING set to   : LAZY
GPU models and configuration : 
GPU 0: NVIDIA H100
GPU 1: NVIDIA H100
GPU 2: NVIDIA H100
GPU 3: NVIDIA H100
GPU 4: NVIDIA H100
GPU 5: NVIDIA H100
GPU 6: NVIDIA H100
GPU 7: NVIDIA H100

Nvidia driver version        : 550.90.07
cuDNN version                : Probably one of the following:
/usr/lib64/libcudnn.so.9.12.0
/usr/lib64/libcudnn_adv.so.9.12.0
/usr/lib64/libcudnn_cnn.so.9.12.0
/usr/lib64/libcudnn_engines_precompiled.so.9.12.0
/usr/lib64/libcudnn_engines_runtime_compiled.so.9.12.0
/usr/lib64/libcudnn_graph.so.9.12.0
/usr/lib64/libcudnn_heuristic.so.9.12.0
/usr/lib64/libcudnn_ops.so.9.12.0
HIP runtime version          : N/A
MIOpen runtime version       : N/A
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      52 bits physical, 57 bits virtual
Byte Order:                         Little Endian
CPU(s):                             368
On-line CPU(s) list:                0-367
Vendor ID:                          AuthenticAMD
Model name:                         AMD EPYC 9654 96-Core Processor
CPU family:                         25
Model:                              17
Thread(s) per core:                 1
Core(s) per socket:                 368
Socket(s):                          1
Stepping:                           1
BogoMIPS:                           4792.79
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm rep_good nopl cpuid extd_apicid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext perfctr_core invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx512_bf16 clzero xsaveerptr wbnoinvd arat npt lbrv nrip_save tsc_scale vmcb_clean flushbyasid pausefilter pfthreshold v_vmsave_vmload vgif vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid fsrm flush_l1d arch_capabilities
Virtualization:                     AMD-V
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          23 MiB (368 instances)
L1i cache:                          23 MiB (368 instances)
L2 cache:                           184 MiB (368 instances)
L3 cache:                           16 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-367
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 Retbleed:             Not affected
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2:           Vulnerable, IBPB: disabled, STIBP: disabled, PBRSB-eIBRS: Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

==============================
Versions of relevant libraries
==============================
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.9.1.4
[pip3] nvidia-cuda-cupti-cu12==12.9.79
[pip3] nvidia-cuda-nvrtc-cu12==12.9.86
[pip3] nvidia-cuda-runtime-cu12==12.9.79
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cufft-cu12==11.4.1.4
[pip3] nvidia-cufile-cu12==1.14.1.1
[pip3] nvidia-curand-cu12==10.3.10.19
[pip3] nvidia-cusolver-cu12==11.7.5.82
[pip3] nvidia-cusparse-cu12==12.5.10.65
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-nccl-cu12==2.27.3
[pip3] nvidia-nvjitlink-cu12==12.9.86
[pip3] nvidia-nvtx-cu12==12.9.79
[pip3] pyzmq==27.1.0
[pip3] torch==2.8.0+cu129
[pip3] torchaudio==2.8.0+cu129
[pip3] torchvision==0.23.0+cu129
[pip3] transformers==4.56.2
[pip3] triton==3.4.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.11.0rc2.dev39+gb1ded114b (git sha: b1ded114b)
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV18    NV18    NV18    NV18    NV18    NV18    NV18    0-367   0               N/A
GPU1    NV18     X      NV18    NV18    NV18    NV18    NV18    NV18    0-367   0               N/A
GPU2    NV18    NV18     X      NV18    NV18    NV18    NV18    NV18    0-367   0               N/A
GPU3    NV18    NV18    NV18     X      NV18    NV18    NV18    NV18    0-367   0               N/A
GPU4    NV18    NV18    NV18    NV18     X      NV18    NV18    NV18    0-367   0               N/A
GPU5    NV18    NV18    NV18    NV18    NV18     X      NV18    NV18    0-367   0               N/A
GPU6    NV18    NV18    NV18    NV18    NV18    NV18     X      NV18    0-367   0               N/A
GPU7    NV18    NV18    NV18    NV18    NV18    NV18    NV18     X      0-367   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

==============================
     Environment Variables
==============================
CUDA_CACHE_PATH=/data/users/myuan/.nv/ComputeCache
CUDA_INCLUDE_DIRS=/usr/local/cuda-12.9/include
PYTORCH_SRC=/home/myuan/src/pytorch
CUDA_NVCC_EXECUTABLE=/home/myuan/ccache/cuda/nvcc
LD_LIBRARY_PATH=/usr/local/cuda-12.9/lib64:
CUDA_CUDART_LIBRARY=/usr/local/cuda-12.9/lib64/libcudart.so
CUDA_HOME=/usr/local/cuda-12.9
CUDA_HOME=/usr/local/cuda-12.9
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY

🐛 Describe the bug

When running

vllm serve Qwen/Qwen2.5-7B --runner pooling --convert reward

There's error

EngineCore_DP0 pid=2362918)   File "/home/myuan/src/vllm/vllm/v1/worker/gpu_model_runner.py", line 3237, in _dummy_pooler_run
(EngineCore_DP0 pid=2362918)     max_task = max(output_size.items(), key=lambda x: x[1])[0]
(EngineCore_DP0 pid=2362918)                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2362918) ValueError: max() iterable argument is empty

Full log in https://gist.github.com/iseeyuan/d21feea9f582a0eae7cddc5089509c09

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[yyzxw]

yes, it has also been reproduced on the latest main branch:

(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712] EngineCore failed to start.
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712] Traceback (most recent call last):
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/v1/engine/core.py", line 703, in run_engine_core
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     engine_core = EngineCoreProc(*args, **kwargs)
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/v1/engine/core.py", line 499, in __init__
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     super().__init__(vllm_config, executor_class, log_stats,
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/v1/engine/core.py", line 93, in __init__
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     self._initialize_kv_caches(vllm_config)
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/v1/engine/core.py", line 191, in _initialize_kv_caches
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     self.model_executor.determine_available_memory())
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/v1/executor/abstract.py", line 85, in determine_available_memory
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     return self.collective_rpc("determine_available_memory")
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/executor/uniproc_executor.py", line 83, in collective_rpc
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     return [run_method(self.driver_worker, method, args, kwargs)]
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/utils/__init__.py", line 3121, in run_method
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     return func(*args, **kwargs)
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]            ^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     return func(*args, **kwargs)
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]            ^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/v1/worker/gpu_worker.py", line 263, in determine_available_memory
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     self.model_runner.profile_run()
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/v1/worker/gpu_model_runner.py", line 3458, in profile_run
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     output = self._dummy_pooler_run(hidden_states)
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     return func(*args, **kwargs)
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]            ^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]   File "/home/jovyan/vllm/vllm/v1/worker/gpu_model_runner.py", line 3385, in _dummy_pooler_run
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]     max_task = max(output_size.items(), key=lambda x: x[1])[0]
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712]                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ERROR 09-29 02:28:32 [core.py:712] ValueError: max() iterable argument is empty
(EngineCore_DP0 pid=2104) Process EngineCore_DP0:
(EngineCore_DP0 pid=2104) Traceback (most recent call last):
(EngineCore_DP0 pid=2104)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/multiprocessing/process.py", line 314, in _bootstrap
(EngineCore_DP0 pid=2104)     self.run()
(EngineCore_DP0 pid=2104)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/multiprocessing/process.py", line 108, in run
(EngineCore_DP0 pid=2104)     self._target(*self._args, **self._kwargs)
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/v1/engine/core.py", line 716, in run_engine_core
(EngineCore_DP0 pid=2104)     raise e
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/v1/engine/core.py", line 703, in run_engine_core
(EngineCore_DP0 pid=2104)     engine_core = EngineCoreProc(*args, **kwargs)
(EngineCore_DP0 pid=2104)                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/v1/engine/core.py", line 499, in __init__
(EngineCore_DP0 pid=2104)     super().__init__(vllm_config, executor_class, log_stats,
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/v1/engine/core.py", line 93, in __init__
(EngineCore_DP0 pid=2104)     self._initialize_kv_caches(vllm_config)
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/v1/engine/core.py", line 191, in _initialize_kv_caches
(EngineCore_DP0 pid=2104)     self.model_executor.determine_available_memory())
(EngineCore_DP0 pid=2104)     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/v1/executor/abstract.py", line 85, in determine_available_memory
(EngineCore_DP0 pid=2104)     return self.collective_rpc("determine_available_memory")
(EngineCore_DP0 pid=2104)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/executor/uniproc_executor.py", line 83, in collective_rpc
(EngineCore_DP0 pid=2104)     return [run_method(self.driver_worker, method, args, kwargs)]
(EngineCore_DP0 pid=2104)             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/utils/__init__.py", line 3121, in run_method
(EngineCore_DP0 pid=2104)     return func(*args, **kwargs)
(EngineCore_DP0 pid=2104)            ^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
(EngineCore_DP0 pid=2104)     return func(*args, **kwargs)
(EngineCore_DP0 pid=2104)            ^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/v1/worker/gpu_worker.py", line 263, in determine_available_memory
(EngineCore_DP0 pid=2104)     self.model_runner.profile_run()
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/v1/worker/gpu_model_runner.py", line 3458, in profile_run
(EngineCore_DP0 pid=2104)     output = self._dummy_pooler_run(hidden_states)
(EngineCore_DP0 pid=2104)              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
(EngineCore_DP0 pid=2104)     return func(*args, **kwargs)
(EngineCore_DP0 pid=2104)            ^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104)   File "/home/jovyan/vllm/vllm/v1/worker/gpu_model_runner.py", line 3385, in _dummy_pooler_run
(EngineCore_DP0 pid=2104)     max_task = max(output_size.items(), key=lambda x: x[1])[0]
(EngineCore_DP0 pid=2104)                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=2104) ValueError: max() iterable argument is empty
[rank0]:[W929 02:28:34.764621850 ProcessGroupNCCL.cpp:1538] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator())
(APIServer pid=1791) Traceback (most recent call last):
(APIServer pid=1791)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/runpy.py", line 198, in _run_module_as_main
(APIServer pid=1791)     return _run_code(code, main_globals, None,
(APIServer pid=1791)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/runpy.py", line 88, in _run_code
(APIServer pid=1791)     exec(code, run_globals)
(APIServer pid=1791)   File "/home/jovyan/.vscode-server/extensions/ms-python.debugpy-2025.10.0/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/__main__.py", line 71, in <module>
(APIServer pid=1791)     cli.main()
(APIServer pid=1791)   File "/home/jovyan/.vscode-server/extensions/ms-python.debugpy-2025.10.0/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py", line 501, in main
(APIServer pid=1791)     run()
(APIServer pid=1791)   File "/home/jovyan/.vscode-server/extensions/ms-python.debugpy-2025.10.0/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py", line 351, in run_file
(APIServer pid=1791)     runpy.run_path(target, run_name="__main__")
(APIServer pid=1791)   File "/home/jovyan/.vscode-server/extensions/ms-python.debugpy-2025.10.0/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 310, in run_path
(APIServer pid=1791)     return _run_module_code(code, init_globals, run_name, pkg_name=pkg_name, script_name=fname)
(APIServer pid=1791)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/.vscode-server/extensions/ms-python.debugpy-2025.10.0/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 127, in _run_module_code
(APIServer pid=1791)     _run_code(code, mod_globals, init_globals, mod_name, mod_spec, pkg_name, script_name)
(APIServer pid=1791)   File "/home/jovyan/.vscode-server/extensions/ms-python.debugpy-2025.10.0/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 118, in _run_code
(APIServer pid=1791)     exec(code, run_globals)
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/entrypoints/openai/api_server.py", line 1953, in <module>
(APIServer pid=1791)     uvloop.run(run_server(args))
(APIServer pid=1791)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/site-packages/uvloop/__init__.py", line 109, in run
(APIServer pid=1791)     return __asyncio.run(
(APIServer pid=1791)            ^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/asyncio/runners.py", line 195, in run
(APIServer pid=1791)     return runner.run(main)
(APIServer pid=1791)            ^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/asyncio/runners.py", line 118, in run
(APIServer pid=1791)     return self._loop.run_until_complete(task)
(APIServer pid=1791)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
(APIServer pid=1791)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/site-packages/uvloop/__init__.py", line 61, in wrapper
(APIServer pid=1791)     return await main
(APIServer pid=1791)            ^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/entrypoints/openai/api_server.py", line 1884, in run_server
(APIServer pid=1791)     await run_server_worker(listen_address, sock, args, **uvicorn_kwargs)
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/entrypoints/openai/api_server.py", line 1902, in run_server_worker
(APIServer pid=1791)     async with build_async_engine_client(
(APIServer pid=1791)                ^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=1791)     return await anext(self.gen)
(APIServer pid=1791)            ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/entrypoints/openai/api_server.py", line 180, in build_async_engine_client
(APIServer pid=1791)     async with build_async_engine_client_from_engine_args(
(APIServer pid=1791)                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=1791)     return await anext(self.gen)
(APIServer pid=1791)            ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/entrypoints/openai/api_server.py", line 225, in build_async_engine_client_from_engine_args
(APIServer pid=1791)     async_llm = AsyncLLM.from_vllm_config(
(APIServer pid=1791)                 ^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/utils/__init__.py", line 1571, in inner
(APIServer pid=1791)     return fn(*args, **kwargs)
(APIServer pid=1791)            ^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/v1/engine/async_llm.py", line 207, in from_vllm_config
(APIServer pid=1791)     return cls(
(APIServer pid=1791)            ^^^^
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/v1/engine/async_llm.py", line 134, in __init__
(APIServer pid=1791)     self.engine_core = EngineCoreClient.make_async_mp_client(
(APIServer pid=1791)                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/v1/engine/core_client.py", line 102, in make_async_mp_client
(APIServer pid=1791)     return AsyncMPClient(*client_args)
(APIServer pid=1791)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/v1/engine/core_client.py", line 769, in __init__
(APIServer pid=1791)     super().__init__(
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/v1/engine/core_client.py", line 448, in __init__
(APIServer pid=1791)     with launch_core_engines(vllm_config, executor_class,
(APIServer pid=1791)          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1791)   File "/home/jovyan/conda-envs/vllm-base/lib/python3.12/contextlib.py", line 144, in __exit__
(APIServer pid=1791)     next(self.gen)
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/v1/engine/utils.py", line 732, in launch_core_engines
(APIServer pid=1791)     wait_for_engine_startup(
(APIServer pid=1791)   File "/home/jovyan/vllm/vllm/v1/engine/utils.py", line 785, in wait_for_engine_startup
(APIServer pid=1791)     raise RuntimeError("Engine core initialization failed. "

[yyzxw]

I will try to fix it

/assign

[noooop]

Sorry for overlooking as_reward_model in #20930

Please try turn off chunked prefill by --no-enable-chunked-prefill to enable the encode api Temporarily.

[iseeyuan]

@noooop thanks! It works with -no-enable-chunked-prefill. @yyzxw hope this info help fix this issue.