[Bug]: vLLM running on Unspecified Platform raises NotImplementedError when using podman/docker-compose

[BastianBN]

Your current environment

The output of `python collect_env.py` (ran on host, not in a container)

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: Rocky Linux 9.5 (Blue Onyx) (x86_64)
GCC version: (GCC) 11.5.0 20240719 (Red Hat 11.5.0-2)
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.34

Python version: 3.9.21 (main, Dec  5 2024, 00:00:00)  [GCC 11.5.0 20240719 (Red Hat 11.5.0-2)] (64-bit runtime)
Python platform: Linux-5.14.0-427.35.1.el9_4.cloud.1.0.x86_64-x86_64-with-glibc2.34
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA L4
Nvidia driver version: 550.90.12
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, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             4
On-line CPU(s) list:                0-3
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) CPU @ 2.20GHz
CPU family:                         6
Model:                              85
Thread(s) per core:                 2
Core(s) per socket:                 2
Socket(s):                          1
Stepping:                           7
BogoMIPS:                           4400.42
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat avx512_vnni md_clear arch_capabilities
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          64 KiB (2 instances)
L1i cache:                          64 KiB (2 instances)
L2 cache:                           2 MiB (2 instances)
L3 cache:                           38.5 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-3
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:      Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Retbleed:             Mitigation; Enhanced 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; Enhanced / Automatic IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown

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==26.3.0
[pip3] torch==2.5.1
[pip3] torchaudio==2.5.1
[pip3] torchvision==0.20.1
[pip3] transformers==4.49.0
[pip3] triton==3.1.0
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.7.3
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      0-3     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/USER/venv/lib/python3.9/site-packages/cv2/../../lib64:
NCCL_CUMEM_ENABLE=0
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY

🐛 Describe the bug

Hi,
I'm trying to run vLLM through podman-compose using the following docker_compose file but I get an "Unspecified platform" message and the pods crashes on startup after raising a NotImplementedError.
I have the same error whether using docker-compose or podman-compose as backends, using the right GPU definition for each (deploy: or device:)
I'm running all of this on a GCP Rocky Linux 9.5 VM. Also, it does work normally (CUDA is detected) when I run the container using podman run -d --name model2 --gpus all --ipc=host -p 8002:8000 --network monitoring-net vllm/vllm-openai:latest --model Qwen/Qwen2.5-Coder-3B-Instruct --gpu-memory-utilization 0.4 --api-key "<...>" --max-model-len 8192 --max-num-seq 64

I made a debug container that doesn't exit the pod when vllm crashes and tried nvidia-smi in but it told me the command doesn't exist, which feels somewhat weird ? I don't know what I can test

docker_compose.yml

# docker-compose.yaml
version: "3"

services:
  model2:
    device:
      - nvidia.com/gpu=all
    image: vllm/vllm-openai:latest
    container_name: model2
    command: >
      --model Qwen/Qwen2.5-Coder-3B-Instruct
      --gpu-memory-utilization 0.4
      --api-key <...>
      --max-model-len 8192
      --max-num-seq 64
      --tensor-parallel-size 1
      --device cuda
    ports:
      - "8002:8000"
    ipc: host
    networks:
      - monitoring-net
    environment:
      - NVIDIA_VISIBLE_DEVICES=ALL
      - CUDA_VISIBLE_DEVICES=ALL

  prometheus:
    image: prom/prometheus:latest
    container_name: prometheus
    command:
      - "--config.file=/etc/prometheus/prometheus.yml"
      - "--storage.tsdb.path=/prometheus"
      - "--web.enable-lifecycle"
    ports:
      - "9090:9090"
    volumes:
      - /home/USER/prometheus/config/prometheus.yaml:/etc/prometheus/prometheus.yml:Z
    networks:
      - monitoring-net

  grafana:
    image: grafana/grafana:latest
    container_name: grafana
    depends_on:
      - prometheus
    ports:
      - "3000:3000"
    environment:
      - GF_SECURITY_ADMIN_PASSWORD=<...>
    networks:
      - monitoring-net

networks:
  monitoring-net:
    driver: bridge

Python/vLLM logs

INFO 03-17 05:44:54 __init__.py:194] No platform detected, vLLM is running on UnspecifiedPlatform
INFO 03-17 05:44:55 api_server.py:840] vLLM API server version 0.7.2
INFO 03-17 05:44:55 api_server.py:841] args: Namespace(host=None, port=8000, uvicorn_log_level='info', allow_credentials=False, allowed_origins=['*'], allowed_methods=['*'], allowed_headers=['*'], api_key='K:i5UHbzkL#Ofv7r', 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, 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, enable_reasoning=False, reasoning_parser=None, tool_call_parser=None, tool_parser_plugin='', model='Qwen/Qwen2.5-Coder-3B-Instruct', task='auto', tokenizer=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, download_dir=None, load_format='auto', config_format=<ConfigFormat.AUTO: 'auto'>, dtype='auto', kv_cache_dtype='auto', max_model_len=8192, guided_decoding_backend='xgrammar', logits_processor_pattern=None, model_impl='auto', distributed_executor_backend=None, pipeline_parallel_size=1, tensor_parallel_size=1, max_parallel_loading_workers=None, ray_workers_use_nsight=False, block_size=None, enable_prefix_caching=None, disable_sliding_window=False, use_v2_block_manager=True, num_lookahead_slots=0, seed=0, swap_space=4, cpu_offload_gb=0, gpu_memory_utilization=0.4, num_gpu_blocks_override=None, max_num_batched_tokens=None, max_num_seqs=64, max_logprobs=20, disable_log_stats=False, quantization=None, rope_scaling=None, rope_theta=None, hf_overrides=None, enforce_eager=False, max_seq_len_to_capture=8192, disable_custom_all_reduce=False, 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='cuda', num_scheduler_steps=1, multi_step_stream_outputs=True, scheduler_delay_factor=0.0, enable_chunked_prefill=None, speculative_model=None, speculative_model_quantization=None, num_speculative_tokens=None, speculative_disable_mqa_scorer=False, speculative_draft_tensor_parallel_size=None, speculative_max_model_len=None, speculative_disable_by_batch_size=None, ngram_prompt_lookup_max=None, ngram_prompt_lookup_min=None, spec_decoding_acceptance_method='rejection_sampler', typical_acceptance_sampler_posterior_threshold=None, typical_acceptance_sampler_posterior_alpha=None, disable_logprobs_during_spec_decoding=None, model_loader_extra_config=None, ignore_patterns=[], preemption_mode=None, served_model_name=None, qlora_adapter_name_or_path=None, otlp_traces_endpoint=None, collect_detailed_traces=None, disable_async_output_proc=False, scheduling_policy='fcfs', override_neuron_config=None, override_pooler_config=None, compilation_config=None, kv_transfer_config=None, worker_cls='auto', generation_config=None, override_generation_config=None, enable_sleep_mode=False, calculate_kv_scales=False, disable_log_requests=False, max_log_len=None, disable_fastapi_docs=False, enable_prompt_tokens_details=False)
INFO 03-17 05:44:55 api_server.py:206] Started engine process with PID 11
INFO 03-17 05:44:59 __init__.py:194] No platform detected, vLLM is running on UnspecifiedPlatform
INFO 03-17 05:45:03 config.py:542] This model supports multiple tasks: {'score', 'embed', 'generate', 'classify', 'reward'}. Defaulting to 'generate'.
Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 911, in <module>
    uvloop.run(run_server(args))
  File "/usr/local/lib/python3.12/dist-packages/uvloop/__init__.py", line 109, in run
    return __asyncio.run(
           ^^^^^^^^^^^^^^
  File "/usr/lib/python3.12/asyncio/runners.py", line 195, in run
    return runner.run(main)
           ^^^^^^^^^^^^^^^^
  File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
    return self._loop.run_until_complete(task)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
  File "/usr/local/lib/python3.12/dist-packages/uvloop/__init__.py", line 61, in wrapper
    return await main
           ^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 875, in run_server
    async with build_async_engine_client(args) as engine_client:
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
    return await anext(self.gen)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 136, in build_async_engine_client
    async with build_async_engine_client_from_engine_args(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
    return await anext(self.gen)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 217, in build_async_engine_client_from_engine_args
    engine_config = engine_args.create_engine_config()
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/engine/arg_utils.py", line 1276, in create_engine_config
    config = VllmConfig(
             ^^^^^^^^^^^
  File "<string>", line 19, in __init__
  File "/usr/local/lib/python3.12/dist-packages/vllm/config.py", line 3206, in __post_init__
    self.model_config.verify_async_output_proc(self.parallel_config,
  File "/usr/local/lib/python3.12/dist-packages/vllm/config.py", line 677, in verify_async_output_proc
    if not current_platform.is_async_output_supported(self.enforce_eager):
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/platforms/interface.py", line 201, in is_async_output_supported
    raise NotImplementedError
NotImplementedError
INFO 03-17 05:45:13 config.py:542] This model supports multiple tasks: {'score', 'classify', 'generate', 'reward', 'embed'}. Defaulting to 'generate'.
ERROR 03-17 05:45:13 engine.py:389] 
Traceback (most recent call last):
  File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 380, in run_mp_engine
    engine = MQLLMEngine.from_engine_args(engine_args=engine_args,
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 118, in from_engine_args
    engine_config = engine_args.create_engine_config(usage_context)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/engine/arg_utils.py", line 1276, in create_engine_config
    config = VllmConfig(
             ^^^^^^^^^^^
  File "<string>", line 19, in __init__
  File "/usr/local/lib/python3.12/dist-packages/vllm/config.py", line 3206, in __post_init__
    self.model_config.verify_async_output_proc(self.parallel_config,
  File "/usr/local/lib/python3.12/dist-packages/vllm/config.py", line 677, in verify_async_output_proc
    if not current_platform.is_async_output_supported(self.enforce_eager):
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/platforms/interface.py", line 201, in is_async_output_supported
    raise NotImplementedError
NotImplementedError
Process SpawnProcess-1:
Traceback (most recent call last):
  File "/usr/lib/python3.12/multiprocessing/process.py", line 314, in _bootstrap
    self.run()
  File "/usr/lib/python3.12/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 391, in run_mp_engine
    raise e
  File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 380, in run_mp_engine
    engine = MQLLMEngine.from_engine_args(engine_args=engine_args,
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 118, in from_engine_args
    engine_config = engine_args.create_engine_config(usage_context)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/engine/arg_utils.py", line 1276, in create_engine_config
    config = VllmConfig(
             ^^^^^^^^^^^
  File "<string>", line 19, in __init__
  File "/usr/local/lib/python3.12/dist-packages/vllm/config.py", line 3206, in __post_init__
    self.model_config.verify_async_output_proc(self.parallel_config,
  File "/usr/local/lib/python3.12/dist-packages/vllm/config.py", line 677, in verify_async_output_proc
    if not current_platform.is_async_output_supported(self.enforce_eager):
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/vllm/platforms/interface.py", line 201, in is_async_output_supported
    raise NotImplementedError
NotImplementedError

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[Prajapati-Deepak]

i'm also facing same issues

[Prajapati-Deepak]

`INFO 03-17 06:04:15 init.py:211] No platform detected, vLLM is running on UnspecifiedPlatform
INFO 03-17 06:04:15 api_server.py:912] vLLM API server version 0.7.3
INFO 03-17 06:04:15 api_server.py:913] args: Namespace(subparser='serve', model_tag='Qwen/Qwen2.5-3B', config='', host=None, port=8000, uvicorn_log_level='info', 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, 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, enable_reasoning=False, reasoning_parser=None, tool_call_parser=None, tool_parser_plugin='', model='Qwen/Qwen2.5-3B', task='auto', tokenizer=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, download_dir=None, load_format='auto', 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=2, max_parallel_loading_workers=None, ray_workers_use_nsight=False, block_size=None, enable_prefix_caching=True, disable_sliding_window=False, use_v2_block_manager=True, num_lookahead_slots=0, seed=0, swap_space=4, cpu_offload_gb=0, gpu_memory_utilization=0.8, 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_overrides=None, enforce_eager=False, max_seq_len_to_capture=8192, disable_custom_all_reduce=False, 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='cuda', num_scheduler_steps=1, multi_step_stream_outputs=True, scheduler_delay_factor=0.0, enable_chunked_prefill=True, speculative_model=None, speculative_model_quantization=None, num_speculative_tokens=None, speculative_disable_mqa_scorer=False, speculative_draft_tensor_parallel_size=None, speculative_max_model_len=None, speculative_disable_by_batch_size=None, ngram_prompt_lookup_max=None, ngram_prompt_lookup_min=None, spec_decoding_acceptance_method='rejection_sampler', typical_acceptance_sampler_posterior_threshold=None, typical_acceptance_sampler_posterior_alpha=None, disable_logprobs_during_spec_decoding=None, model_loader_extra_config=None, ignore_patterns=[], preemption_mode=None, served_model_name=None, qlora_adapter_name_or_path=None, otlp_traces_endpoint=None, collect_detailed_traces=None, disable_async_output_proc=True, 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', generation_config=None, override_generation_config=None, enable_sleep_mode=False, calculate_kv_scales=False, additional_config=None, disable_log_requests=True, max_log_len=None, disable_fastapi_docs=False, enable_prompt_tokens_details=False, dispatch_function=<function ServeSubcommand.cmd at 0x7f19ef925620>)
INFO 03-17 06:04:15 api_server.py:209] Started engine process with PID 77
INFO 03-17 06:04:19 init.py:211] No platform detected, vLLM is running on UnspecifiedPlatform
INFO 03-17 06:04:22 config.py:549] This model supports multiple tasks: {'embed', 'score', 'generate', 'classify', 'reward'}. Defaulting to 'generate'.
INFO 03-17 06:04:22 config.py:1382] Defaulting to use mp for distributed inference
INFO 03-17 06:04:22 config.py:1555] Chunked prefill is enabled with max_num_batched_tokens=2048.
INFO 03-17 06:04:24 config.py:549] This model supports multiple tasks: {'reward', 'generate', 'embed', 'classify', 'score'}. Defaulting to 'generate'.
INFO 03-17 06:04:24 config.py:1382] Defaulting to use mp for distributed inference
INFO 03-17 06:04:24 config.py:1555] Chunked prefill is enabled with max_num_batched_tokens=2048.
INFO 03-17 06:04:25 llm_engine.py:234] Initializing a V0 LLM engine (v0.7.3) with config: model='Qwen/Qwen2.5-3B', speculative_config=None, tokenizer='Qwen/Qwen2.5-3B', 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=32768, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=2, 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'), observability_config=ObservabilityConfig(otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=0, served_model_name=Qwen/Qwen2.5-3B, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=True, chunked_prefill_enabled=True, use_async_output_proc=False, 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,
WARNING 03-17 06:04:32 multiproc_worker_utils.py:300] Reducing Torch parallelism from 64 threads to 1 to avoid unnecessary CPU contention. Set OMP_NUM_THREADS in the external environment to tune this value as needed.
INFO 03-17 06:04:32 custom_cache_manager.py:19] Setting Triton cache manager to: vllm.triton_utils.custom_cache_manager:CustomCacheManager
ERROR 03-17 06:04:32 engine.py:400] not enough values to unpack (expected 2, got 1)
ERROR 03-17 06:04:32 engine.py:400] Traceback (most recent call last):
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 391, in run_mp_engine
ERROR 03-17 06:04:32 engine.py:400] engine = MQLLMEngine.from_engine_args(engine_args=engine_args,
ERROR 03-17 06:04:32 engine.py:400] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 124, in from_engine_args
ERROR 03-17 06:04:32 engine.py:400] return cls(ipc_path=ipc_path,
ERROR 03-17 06:04:32 engine.py:400] ^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 76, in init
ERROR 03-17 06:04:32 engine.py:400] self.engine = LLMEngine(*args, **kwargs)
ERROR 03-17 06:04:32 engine.py:400] ^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/engine/llm_engine.py", line 273, in init
ERROR 03-17 06:04:32 engine.py:400] self.model_executor = executor_class(vllm_config=vllm_config, )
ERROR 03-17 06:04:32 engine.py:400] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/executor/executor_base.py", line 271, in init
ERROR 03-17 06:04:32 engine.py:400] super().init(*args, **kwargs)
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/executor/executor_base.py", line 52, in init
ERROR 03-17 06:04:32 engine.py:400] self._init_executor()
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/executor/mp_distributed_executor.py", line 123, in _init_executor
ERROR 03-17 06:04:32 engine.py:400] self._run_workers("init_worker", all_kwargs)
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/executor/mp_distributed_executor.py", line 185, in _run_workers
ERROR 03-17 06:04:32 engine.py:400] driver_worker_output = run_method(self.driver_worker, sent_method,
ERROR 03-17 06:04:32 engine.py:400] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/utils.py", line 2196, in run_method
ERROR 03-17 06:04:32 engine.py:400] return func(*args, **kwargs)
ERROR 03-17 06:04:32 engine.py:400] ^^^^^^^^^^^^^^^^^^^^^
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/worker/worker_base.py", line 558, in init_worker
ERROR 03-17 06:04:32 engine.py:400] worker_class = resolve_obj_by_qualname(
ERROR 03-17 06:04:32 engine.py:400] ^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 03-17 06:04:32 engine.py:400] File "/usr/local/lib/python3.12/dist-packages/vllm/utils.py", line 1876, in resolve_obj_by_qualname
ERROR 03-17 06:04:32 engine.py:400] module_name, obj_name = qualname.rsplit(".", 1)
ERROR 03-17 06:04:32 engine.py:400] ^^^^^^^^^^^^^^^^^^^^^
ERROR 03-17 06:04:32 engine.py:400] ValueError: not enough values to unpack (expected 2, got 1)
Process SpawnProcess-1:
ERROR 03-17 06:04:32 multiproc_worker_utils.py:124] Worker VllmWorkerProcess pid 351 died, exit code: -15
INFO 03-17 06:04:32 multiproc_worker_utils.py:128] Killing local vLLM worker processes
Traceback (most recent call last):
File "/usr/lib/python3.12/multiprocessing/process.py", line 314, in _bootstrap
self.run()
File "/usr/lib/python3.12/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 402, in run_mp_engine
raise e
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 391, in run_mp_engine
engine = MQLLMEngine.from_engine_args(engine_args=engine_args,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 124, in from_engine_args
return cls(ipc_path=ipc_path,
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 76, in init
self.engine = LLMEngine(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/llm_engine.py", line 273, in init
self.model_executor = executor_class(vllm_config=vllm_config, )
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/executor/executor_base.py", line 271, in init
super().init(*args, **kwargs)
File "/usr/local/lib/python3.12/dist-packages/vllm/executor/executor_base.py", line 52, in init
self._init_executor()
File "/usr/local/lib/python3.12/dist-packages/vllm/executor/mp_distributed_executor.py", line 123, in _init_executor
self._run_workers("init_worker", all_kwargs)
File "/usr/local/lib/python3.12/dist-packages/vllm/executor/mp_distributed_executor.py", line 185, in _run_workers
driver_worker_output = run_method(self.driver_worker, sent_method,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/utils.py", line 2196, in run_method
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/worker/worker_base.py", line 558, in init_worker
worker_class = resolve_obj_by_qualname(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/utils.py", line 1876, in resolve_obj_by_qualname
module_name, obj_name = qualname.rsplit(".", 1)
^^^^^^^^^^^^^^^^^^^^^
ValueError: not enough values to unpack (expected 2, got 1)
Traceback (most recent call last):
File "/usr/local/bin/vllm", line 10, in
sys.exit(main())
^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/cli/main.py", line 73, in main
args.dispatch_function(args)
File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/cli/serve.py", line 34, in cmd
uvloop.run(run_server(args))
File "/usr/local/lib/python3.12/dist-packages/uvloop/init.py", line 109, in run
return __asyncio.run(
^^^^^^^^^^^^^^
File "/usr/lib/python3.12/asyncio/runners.py", line 195, in run
return runner.run(main)
^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
File "/usr/local/lib/python3.12/dist-packages/uvloop/init.py", line 61, in wrapper
return await main
^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 947, in run_server
async with build_async_engine_client(args) as engine_client:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/contextlib.py", line 210, in aenter
return await anext(self.gen)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 139, in build_async_engine_client
async with build_async_engine_client_from_engine_args(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/contextlib.py", line 210, in aenter
return await anext(self.gen)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 233, in build_async_engine_client_from_engine_args
raise RuntimeError(
RuntimeError: Engine process failed to start. See stack trace for the root cause.```

[Symfomany]

+1

[yankay]

HI @BastianBN

If you cannot run nvidia-smi with the container, it means the container cannot use GPU.

You can follow the https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html to config the podman, and then ensure the sample cuda workload can be run successfully.

And then the compose.yaml needs to add the --security-opt=label=disable for podman.

[BastianBN]

HI @BastianBN

If you cannot run nvidia-smi with the container, it means the container cannot use GPU.

You can follow the https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html to config the podman, and then ensure the sample cuda workload can be run successfully.

And then the compose.yaml needs to add the --security-opt=label=disable for podman.

Hello @yankay
I just tried to add the security-opt option but it doesn't seem to work any better. The weird thing is that I cannot use the GPU only when I start the container using podman compose up -d, it does work when I do podman run with the exact same image and arguments given to vLLM. If that was an nvidia drivers problem, it probably wouldn't work even with podman run, right ?

[yankay]

It seems the same as containers/podman#25196. If it's a podman issue, it's better to discussit in the Podman issue.

[tuliren]

It seems the same as containers/podman#25196. If it's a podman issue, it's better to discussit in the Podman issue.

No, this is not a podman only issue. I use plain docker / docker compose and have run into the same error.