[Bug]: Engine fails to start when running Qwen2.5 Deepseek r1

[JamesDConley]

Your current environment

The output of `python collect_env.py (run within the docker container)`

root@29c31f05a333:/vllm-workspace# python3 collect_env.py
INFO 01-29 07:36:38 __init__.py:183] Automatically detected platform cuda.
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 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.12.8 (main, Dec  4 2024, 08:54:12) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.8.0-51-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA RTX A6000
GPU 1: NVIDIA RTX A6000

Nvidia driver version: 535.183.01
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:                        43 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               12
On-line CPU(s) list:                  0-11
Vendor ID:                            AuthenticAMD
Model name:                           AMD Ryzen 5 3600 6-Core Processor
CPU family:                           23
Model:                                113
Thread(s) per core:                   2
Core(s) per socket:                   6
Socket(s):                            1
Stepping:                             0
Frequency boost:                      enabled
CPU max MHz:                          4208.2031
CPU min MHz:                          2200.0000
BogoMIPS:                             7186.04
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 constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sev sev_es
Virtualization:                       AMD-V
L1d cache:                            192 KiB (6 instances)
L1i cache:                            192 KiB (6 instances)
L2 cache:                             3 MiB (6 instances)
L3 cache:                             32 MiB (2 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-11
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:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
Vulnerability Spec rstack overflow:   Mitigation; Safe RET
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; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] flashinfer==0.1.6+cu121torch2.4
[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-ml-py==12.570.86
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pyzmq==26.2.0
[pip3] torch==2.5.1
[pip3] torchvision==0.20.1
[pip3] transformers==4.48.1
[pip3] triton==3.1.0
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.7.0
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0	GPU1	CPU Affinity	NUMA Affinity	GPU NUMA ID
GPU0	 X 	NV4	0-11	0		N/A
GPU1	NV4	 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

NVIDIA_VISIBLE_DEVICES=all
NVIDIA_REQUIRE_CUDA=cuda>=12.1 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526
NVIDIA_DRIVER_CAPABILITIES=compute,utility
VLLM_USAGE_SOURCE=production-docker-image
CUDA_VERSION=12.1.0
LD_LIBRARY_PATH=/usr/local/lib/python3.12/dist-packages/cv2/../../lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
NCCL_CUMEM_ENABLE=0
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY

Model Input Dumps

N/a

🐛 Describe the bug

I have been running vllm for some time using docker, and I recently pulled the latest version to try a new model.
The engine fails to start after loading the model with much room to spare memory wise.

Here is the entrypoint in my docker-compose

entrypoint: ["python3", "-m", "vllm.entrypoints.openai.api_server", "--model", "/models/DeepSeek-R1-Distill-Qwen-32B", "--dtype", "float16", "-tp", "2", "--chat-template", "/chat_templates/qwen2.5-instruct.jinja", "--max-model-len", "1000", "--gpu-memory-utilization", "0.9", "--swap-space", "36", "--guided-decoding-backend", "lm-format-enforcer"]

Here is the full log from the container

INFO 01-29 07:13:04 __init__.py:183] Automatically detected platform cuda.
INFO 01-29 07:13:05 api_server.py:835] vLLM API server version 0.7.0
INFO 01-29 07:13:05 api_server.py:836] args: Namespace(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='/chat_templates/qwen2.5-instruct.jinja', 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, tool_call_parser=None, tool_parser_plugin='', model='/models/DeepSeek-R1-Distill-Qwen-32B', 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='float16', kv_cache_dtype='auto', max_model_len=1000, guided_decoding_backend='lm-format-enforcer', logits_processor_pattern=None, 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=None, disable_sliding_window=False, use_v2_block_manager=True, num_lookahead_slots=0, seed=0, swap_space=36.0, cpu_offload_gb=0, gpu_memory_utilization=0.9, num_gpu_blocks_override=None, max_num_batched_tokens=None, 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='auto', 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, 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 01-29 07:13:05 api_server.py:203] Started engine process with PID 25
WARNING 01-29 07:13:05 config.py:2318] Casting torch.bfloat16 to torch.float16.
INFO 01-29 07:13:08 __init__.py:183] Automatically detected platform cuda.
WARNING 01-29 07:13:09 config.py:2318] Casting torch.bfloat16 to torch.float16.
INFO 01-29 07:13:10 config.py:520] This model supports multiple tasks: {'score', 'classify', 'reward', 'generate', 'embed'}. Defaulting to 'generate'.
INFO 01-29 07:13:10 config.py:1328] Defaulting to use mp for distributed inference
WARNING 01-29 07:13:10 config.py:1075] Possibly too large swap space. 72.00 GiB out of the 125.71 GiB total CPU memory is allocated for the swap space.
INFO 01-29 07:13:14 config.py:520] This model supports multiple tasks: {'classify', 'generate', 'score', 'reward', 'embed'}. Defaulting to 'generate'.
INFO 01-29 07:13:14 config.py:1328] Defaulting to use mp for distributed inference
WARNING 01-29 07:13:14 config.py:1075] Possibly too large swap space. 72.00 GiB out of the 125.71 GiB total CPU memory is allocated for the swap space.
INFO 01-29 07:13:14 llm_engine.py:232] Initializing an LLM engine (v0.7.0) with config: model='/models/DeepSeek-R1-Distill-Qwen-32B', speculative_config=None, tokenizer='/models/DeepSeek-R1-Distill-Qwen-32B', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=1000, 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='lm-format-enforcer'), observability_config=ObservabilityConfig(otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=0, served_model_name=/models/DeepSeek-R1-Distill-Qwen-32B, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=False, 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, 
WARNING 01-29 07:13:15 multiproc_worker_utils.py:298] Reducing Torch parallelism from 6 threads to 1 to avoid unnecessary CPU contention. Set OMP_NUM_THREADS in the external environment to tune this value as needed.
INFO 01-29 07:13:15 custom_cache_manager.py:17] Setting Triton cache manager to: vllm.triton_utils.custom_cache_manager:CustomCacheManager
(VllmWorkerProcess pid=90) INFO 01-29 07:13:15 multiproc_worker_utils.py:227] Worker ready; awaiting tasks
INFO 01-29 07:13:15 cuda.py:225] Using Flash Attention backend.
(VllmWorkerProcess pid=90) INFO 01-29 07:13:15 cuda.py:225] Using Flash Attention backend.
(VllmWorkerProcess pid=90) INFO 01-29 07:13:16 utils.py:938] Found nccl from library libnccl.so.2
INFO 01-29 07:13:16 utils.py:938] Found nccl from library libnccl.so.2
(VllmWorkerProcess pid=90) INFO 01-29 07:13:16 pynccl.py:67] vLLM is using nccl==2.21.5
INFO 01-29 07:13:16 pynccl.py:67] vLLM is using nccl==2.21.5
INFO 01-29 07:13:16 custom_all_reduce_utils.py:204] generating GPU P2P access cache in /root/.cache/vllm/gpu_p2p_access_cache_for_0,1.json
INFO 01-29 07:13:25 custom_all_reduce_utils.py:242] reading GPU P2P access cache from /root/.cache/vllm/gpu_p2p_access_cache_for_0,1.json
(VllmWorkerProcess pid=90) INFO 01-29 07:13:25 custom_all_reduce_utils.py:242] reading GPU P2P access cache from /root/.cache/vllm/gpu_p2p_access_cache_for_0,1.json
INFO 01-29 07:13:25 shm_broadcast.py:256] vLLM message queue communication handle: Handle(connect_ip='127.0.0.1', local_reader_ranks=[1], buffer_handle=(1, 4194304, 6, 'psm_88515be3'), local_subscribe_port=45365, remote_subscribe_port=None)
INFO 01-29 07:13:25 model_runner.py:1110] Starting to load model /models/DeepSeek-R1-Distill-Qwen-32B...
(VllmWorkerProcess pid=90) INFO 01-29 07:13:25 model_runner.py:1110] Starting to load model /models/DeepSeek-R1-Distill-Qwen-32B...
Loading safetensors checkpoint shards:   0% Completed | 0/8 [00:00<?, ?it/s]
Loading safetensors checkpoint shards:  12% Completed | 1/8 [00:24<02:52, 24.69s/it]
Loading safetensors checkpoint shards:  25% Completed | 2/8 [00:51<02:35, 25.86s/it]
Loading safetensors checkpoint shards:  38% Completed | 3/8 [01:18<02:12, 26.46s/it]
Loading safetensors checkpoint shards:  50% Completed | 4/8 [01:44<01:45, 26.26s/it]
Loading safetensors checkpoint shards:  62% Completed | 5/8 [02:11<01:19, 26.45s/it]
Loading safetensors checkpoint shards:  75% Completed | 6/8 [02:22<00:42, 21.44s/it]
Loading safetensors checkpoint shards:  88% Completed | 7/8 [02:49<00:23, 23.04s/it]
Loading safetensors checkpoint shards: 100% Completed | 8/8 [03:15<00:00, 24.12s/it]
Loading safetensors checkpoint shards: 100% Completed | 8/8 [03:15<00:00, 24.47s/it]

INFO 01-29 07:16:42 model_runner.py:1115] Loading model weights took 30.7293 GB
(VllmWorkerProcess pid=90) INFO 01-29 07:16:42 model_runner.py:1115] Loading model weights took 30.7293 GB
(VllmWorkerProcess pid=90) INFO 01-29 07:16:47 worker.py:266] Memory profiling takes 4.54 seconds
(VllmWorkerProcess pid=90) INFO 01-29 07:16:47 worker.py:266] the current vLLM instance can use total_gpu_memory (47.53GiB) x gpu_memory_utilization (0.90) = 42.78GiB
(VllmWorkerProcess pid=90) INFO 01-29 07:16:47 worker.py:266] model weights take 30.73GiB; non_torch_memory takes 0.38GiB; PyTorch activation peak memory takes 0.26GiB; the rest of the memory reserved for KV Cache is 11.41GiB.
INFO 01-29 07:16:47 worker.py:266] Memory profiling takes 4.66 seconds
INFO 01-29 07:16:47 worker.py:266] the current vLLM instance can use total_gpu_memory (47.54GiB) x gpu_memory_utilization (0.90) = 42.78GiB
INFO 01-29 07:16:47 worker.py:266] model weights take 30.73GiB; non_torch_memory takes 0.41GiB; PyTorch activation peak memory takes 1.41GiB; the rest of the memory reserved for KV Cache is 10.24GiB.
INFO 01-29 07:16:47 executor_base.py:108] # CUDA blocks: 5242, # CPU blocks: 18432
INFO 01-29 07:16:47 executor_base.py:113] Maximum concurrency for 1000 tokens per request: 83.87x
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 899, 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 194, 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 863, 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 133, 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 227, in build_async_engine_client_from_engine_args
    raise RuntimeError(
RuntimeError: Engine process failed to start. See stack trace for the root cause.

I have also tried removing the guided decoding backend specification and received the same stack trace.

No other processes are using the GPU. Even the gdm service is stopped (I am sshed into the server)

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