[Bug]: Error Running Llama 3.2 1B on CPU

[kunalmohan]

Your current environment

The output of `python collect_env.py`

PyTorch version: 2.4.0+cpu
Is debug build: False
CUDA used to build PyTorch: None
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: Could not collect
CMake version: version 3.30.4
Libc version: glibc-2.35

Python version: 3.10.14 (main, May  6 2024, 19:42:50) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.5.0-1025-azure-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
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:                      48 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             4
On-line CPU(s) list:                0-3
Vendor ID:                          AuthenticAMD
Model name:                         AMD EPYC 7763 64-Core Processor
CPU family:                         25
Model:                              1
Thread(s) per core:                 2
Core(s) per socket:                 2
Socket(s):                          1
Stepping:                           1
BogoMIPS:                           4890.86
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 tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext invpcid_single vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves clzero xsaveerptr rdpru arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload umip vaes vpclmulqdq rdpid fsrm
Virtualization:                     AMD-V
Hypervisor vendor:                  Microsoft
Virtualization type:                full
L1d cache:                          64 KiB (2 instances)
L1i cache:                          64 KiB (2 instances)
L2 cache:                           1 MiB (2 instances)
L3 cache:                           32 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:      Not affected
Vulnerability Retbleed:             Not affected
Vulnerability Spec rstack overflow: Vulnerable: Safe RET, no microcode
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] intel_extension_for_pytorch==2.4.0
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.1.3.1
[pip3] nvidia-cuda-cupti-cu12==12.1.105
[pip3] nvidia-cuda-nvrtc-cu12==12.1.105
[pip3] nvidia-cuda-runtime-cu12==12.1.105
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.0.2.54
[pip3] nvidia-curand-cu12==10.3.2.106
[pip3] nvidia-cusolver-cu12==11.4.5.107
[pip3] nvidia-cusparse-cu12==12.1.0.106
[pip3] nvidia-ml-py==12.560.30
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] nvidia-nvjitlink-cu12==12.6.77
[pip3] nvidia-nvtx-cu12==12.1.105
[pip3] pyzmq==26.2.0
[pip3] torch==2.4.0+cpu
[pip3] torchaudio==2.4.0+cpu
[pip3] torchvision==0.19.0+cpu
[pip3] transformers==4.46.0.dev0
[pip3] triton==3.0.0
[conda] intel-extension-for-pytorch 2.4.0                    pypi_0    pypi
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] nvidia-cublas-cu12        12.1.3.1                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.1.105                 pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.1.105                 pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.1.105                 pypi_0    pypi
[conda] nvidia-cudnn-cu12         9.1.0.70                 pypi_0    pypi
[conda] nvidia-cufft-cu12         11.0.2.54                pypi_0    pypi
[conda] nvidia-curand-cu12        10.3.2.106               pypi_0    pypi
[conda] nvidia-cusolver-cu12      11.4.5.107               pypi_0    pypi
[conda] nvidia-cusparse-cu12      12.1.0.106               pypi_0    pypi
[conda] nvidia-ml-py              12.560.30                pypi_0    pypi
[conda] nvidia-nccl-cu12          2.20.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.6.77                  pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.1.105                 pypi_0    pypi
[conda] pyzmq                     26.2.0                   pypi_0    pypi
[conda] torch                     2.4.0+cpu                pypi_0    pypi
[conda] torchaudio                2.4.0+cpu                pypi_0    pypi
[conda] torchvision               0.19.0+cpu               pypi_0    pypi
[conda] transformers              4.46.0.dev0              pypi_0    pypi
[conda] triton                    3.0.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.3.dev65+g7f60520d
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
Could not collect

Model Input Dumps

No response

🐛 Describe the bug

Installed vllm for CPU as mentioned in https://docs.vllm.ai/en/latest/getting_started/cpu-installation.html#

Error when running Llama-3.2-1B on CPU.
Command:

vllm serve meta-llama/Llama-3.2-1B-Instruct --port 8080 --api-key qwerty123  --max-model-len=30000

Error:

INFO 10-03 07:38:10 logger.py:36] Received request chat-3361fcfb910c48b08a00e19e7f79c6e0: prompt: '<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date: December 2023\nToday Date: 03 Oct 2024\n\n<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nExplain the significance of AI in modern technology.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n', params: SamplingParams(n=1, best_of=1, presence_penalty=0.0, frequency_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.9, top_k=-1, min_p=0.0, seed=None, use_beam_search=False, length_penalty=1.0, early_stopping=False, stop=[], stop_token_ids=[], include_stop_str_in_output=False, ignore_eos=False, max_tokens=1000, min_tokens=0, logprobs=None, prompt_logprobs=None, skip_special_tokens=True, spaces_between_special_tokens=True, truncate_prompt_tokens=None), guided_decoding=GuidedDecodingParams(json=None, regex=None, choice=None, grammar=None, json_object=None, backend=None, whitespace_pattern=None), prompt_token_ids: [128000, 128006, 9125, 128007, 271, 38766, 1303, 33025, 2696, 25, 6790, 220, 2366, 18, 198, 15724, 2696, 25, 220, 2839, 5020, 220, 2366, 19, 271, 128009, 128006, 882, 128007, 271, 849, 21435, 279, 26431, 315, 15592, 304, 6617, 5557, 13, 128009, 128006, 78191, 128007, 271], lora_request: None, prompt_adapter_request: None.
INFO 10-03 07:38:12 engine.py:288] Added request chat-3361fcfb910c48b08a00e19e7f79c6e0.
ERROR 10-03 07:38:34 client.py:247] RuntimeError('Engine loop has died')
ERROR 10-03 07:38:34 client.py:247] Traceback (most recent call last):
ERROR 10-03 07:38:34 client.py:247]   File "/home/azureuser/miniconda3/envs/myenv/lib/python3.10/site-packages/vllm-0.6.3.dev65+g7f60520d.cpu-py3.10-linux-x86_64.egg/vllm/engine/multiprocessing/client.py", line 147, in run_heartbeat_loop
ERROR 10-03 07:38:34 client.py:247]     await self._check_success(
ERROR 10-03 07:38:34 client.py:247]   File "/home/azureuser/miniconda3/envs/myenv/lib/python3.10/site-packages/vllm-0.6.3.dev65+g7f60520d.cpu-py3.10-linux-x86_64.egg/vllm/engine/multiprocessing/client.py", line 311, in _check_success
ERROR 10-03 07:38:34 client.py:247]     raise response
ERROR 10-03 07:38:34 client.py:247] RuntimeError: Engine loop has died
CRITICAL 10-03 07:38:38 launcher.py:99] MQLLMEngine is already dead, terminating server process

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[kunalmohan]

Same issue with vllm version 0.6.2+cpu

[DarkLight1337]

Can you check whether it's fixed by #9044?

[DarkLight1337]

If the issue persists, please show the full stack trace of the error.

[kunalmohan]

Nope, it does not fix the issue. I've pasted the complete stacktrace in the issue description. Pasting it again:

INFO:     Uvicorn running on http://0.0.0.0:8081 (Press CTRL+C to quit)
INFO 10-04 06:33:09 logger.py:36] Received request chat-32e960f7889940598a1ac749e5726a01: prompt: '<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date: December 2023\nToday Date: 04 Oct 2024\n\n<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nExplain the significance of AI in modern technology.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n', params: SamplingParams(n=1, best_of=1, presence_penalty=0.0, frequency_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.9, top_k=-1, min_p=0.0, seed=None, use_beam_search=False, length_penalty=1.0, early_stopping=False, stop=[], stop_token_ids=[], include_stop_str_in_output=False, ignore_eos=False, max_tokens=1000, min_tokens=0, logprobs=None, prompt_logprobs=None, skip_special_tokens=True, spaces_between_special_tokens=True, truncate_prompt_tokens=None), guided_decoding=GuidedDecodingParams(json=None, regex=None, choice=None, grammar=None, json_object=None, backend=None, whitespace_pattern=None), prompt_token_ids: [128000, 128006, 9125, 128007, 271, 38766, 1303, 33025, 2696, 25, 6790, 220, 2366, 18, 198, 15724, 2696, 25, 220, 2371, 5020, 220, 2366, 19, 271, 128009, 128006, 882, 128007, 271, 849, 21435, 279, 26431, 315, 15592, 304, 6617, 5557, 13, 128009, 128006, 78191, 128007, 271], lora_request: None, prompt_adapter_request: None.
INFO 10-04 06:33:15 engine.py:288] Added request chat-32e960f7889940598a1ac749e5726a01.
ERROR 10-04 06:33:36 client.py:247] RuntimeError('Engine loop has died')
ERROR 10-04 06:33:36 client.py:247] Traceback (most recent call last):
ERROR 10-04 06:33:36 client.py:247]   File "/home/azureuser/miniconda3/envs/myenv/lib/python3.10/site-packages/vllm-0.6.3.dev65+g7f60520d.d20241004.cpu-py3.10-linux-x86_64.egg/vllm/engine/multiprocessing/client.py", line 147, in run_heartbeat_loop
ERROR 10-04 06:33:36 client.py:247]     await self._check_success(
ERROR 10-04 06:33:36 client.py:247]   File "/home/azureuser/miniconda3/envs/myenv/lib/python3.10/site-packages/vllm-0.6.3.dev65+g7f60520d.d20241004.cpu-py3.10-linux-x86_64.egg/vllm/engine/multiprocessing/client.py", line 311, in _check_success
ERROR 10-04 06:33:36 client.py:247]     raise response
ERROR 10-04 06:33:36 client.py:247] RuntimeError: Engine loop has died
INFO 10-04 06:33:43 metrics.py:351] Avg prompt throughput: 1.2 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 1 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%.
CRITICAL 10-04 06:33:45 launcher.py:99] MQLLMEngine is already dead, terminating server process
INFO:     xx.xx.xx.xx:xx - "POST /v1/chat/completions HTTP/1.1" 500 Internal Server Error
INFO:     Shutting down
INFO:     Waiting for application shutdown.
INFO:     Application shutdown complete.
INFO:     Finished server process [1063]

[DarkLight1337]

@robertgshaw2-neuralmagic seems that MQLLMEngine is hiding the stack trace... can we avoid this to make debugging easier?

[bpucla]

Any update on the issue? Have the same issue (exactly same stack trace) with Llama2 inference with vllm-0.6.1 on GPU.

[Kepontry]

@bpucla Hi, have you tried #9044, that pull solved my problem. I'm working on vllm 0.6.2+cpu.

[vrtust]

Same error and log.
Set VLLM_RPC_TIMEOUT=100000 solve it, just like:

VLLM_RPC_TIMEOUT=100000 python -m vllm.entrypoints.openai.api_server --port 8080 --served-model-name Qwen2-7B-Instruct --model /workspace/model/Qwen2-7B-Instruct --tensor-parallel-size 1 --dtype half

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[github-actions]

This issue has been automatically closed due to inactivity. Please feel free to reopen if you feel it is still relevant. Thank you!