[Bug]: Phi3 still not supported

[andrew-vold]

Your current environment

PyTorch version: 2.2.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
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: version 3.29.2
Libc version: glibc-2.35

Python version: 3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-1041-nvidia-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.1.66
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A100-SXM4-40GB
GPU 1: NVIDIA A100-SXM4-40GB
GPU 2: NVIDIA A100-SXM4-40GB
GPU 3: NVIDIA A100-SXM4-40GB
GPU 4: NVIDIA A100-SXM4-40GB
GPU 5: NVIDIA A100-SXM4-40GB
GPU 6: NVIDIA A100-SXM4-40GB
GPU 7: NVIDIA A100-SXM4-40GB

Nvidia driver version: 525.147.05
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):                             256
On-line CPU(s) list:                0-255
Vendor ID:                          AuthenticAMD
Model name:                         AMD EPYC 7742 64-Core Processor
CPU family:                         23
Model:                              49
Thread(s) per core:                 2
Core(s) per socket:                 64
Socket(s):                          2
Stepping:                           0
Frequency boost:                    enabled
CPU max MHz:                        2250.0000
CPU min MHz:                        1500.0000
BogoMIPS:                           4491.63
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 ibrs 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 amd_ppin 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 sme sev sev_es
Virtualization:                     AMD-V
L1d cache:                          4 MiB (128 instances)
L1i cache:                          4 MiB (128 instances)
L2 cache:                           64 MiB (128 instances)
L3 cache:                           512 MiB (32 instances)
NUMA node(s):                       8
NUMA node0 CPU(s):                  0-15,128-143
NUMA node1 CPU(s):                  16-31,144-159
NUMA node2 CPU(s):                  32-47,160-175
NUMA node3 CPU(s):                  48-63,176-191
NUMA node4 CPU(s):                  64-79,192-207
NUMA node5 CPU(s):                  80-95,208-223
NUMA node6 CPU(s):                  96-111,224-239
NUMA node7 CPU(s):                  112-127,240-255
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:             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 and seccomp
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
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] nvidia-nccl-cu12==2.19.3
[pip3] torch==2.2.1
[pip3] torchaudio==2.1.2
[pip3] torchvision==0.16.2
[pip3] triton==2.2.0
[pip3] vllm-nccl-cu12==2.18.1.0.4.0
[conda] blas                      1.0                         mkl  
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] libjpeg-turbo             2.0.0                h9bf148f_0    pytorch
[conda] mkl                       2023.1.0         h213fc3f_46344  
[conda] mkl-service               2.4.0           py310h5eee18b_1  
[conda] mkl_fft                   1.3.8           py310h5eee18b_0  
[conda] mkl_random                1.2.4           py310hdb19cb5_0  
[conda] numpy                     1.26.4          py310h5f9d8c6_0  
[conda] numpy-base                1.26.4          py310hb5e798b_0  
[conda] nvidia-nccl-cu12          2.19.3                   pypi_0    pypi
[conda] pytorch-cuda              12.1                 ha16c6d3_5    pytorch
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torch                     2.2.1                    pypi_0    pypi
[conda] torchaudio                2.1.2               py310_cu121    pytorch
[conda] torchvision               0.16.2              py310_cu121    pytorch
[conda] triton                    2.2.0                    pypi_0    pypi
[conda] vllm-nccl-cu12            2.18.1.0.4.0             pypi_0    pypiROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.4.1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    NIC0    NIC1    NIC2    NIC3    NIC4    NIC5    NIC6    NIC7    NIC8    NIC9    CPU Affinity       NUMA Affinity
GPU0     X      NV12    NV12    NV12    NV12    NV12    NV12    NV12    PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     48-63,176-191      3
GPU1    NV12     X      NV12    NV12    NV12    NV12    NV12    NV12    PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     48-63,176-191      3
GPU2    NV12    NV12     X      NV12    NV12    NV12    NV12    NV12    SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS     16-31,144-159      1
GPU3    NV12    NV12    NV12     X      NV12    NV12    NV12    NV12    SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS     16-31,144-159      1
GPU4    NV12    NV12    NV12    NV12     X      NV12    NV12    NV12    SYS     SYS     SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     112-127,240-255    7
GPU5    NV12    NV12    NV12    NV12    NV12     X      NV12    NV12    SYS     SYS     SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     112-127,240-255    7
GPU6    NV12    NV12    NV12    NV12    NV12    NV12     X      NV12    SYS     SYS     SYS     SYS     SYS     SYS     PXB     PXB     SYS     SYS     80-95,208-223      5
GPU7    NV12    NV12    NV12    NV12    NV12    NV12    NV12     X      SYS     SYS     SYS     SYS     SYS     SYS     PXB     PXB     SYS     SYS     80-95,208-223      5
NIC0    PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS      X      PXB     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS
NIC1    PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS     PXB      X      SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS
NIC2    SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS      X      PXB     SYS     SYS     SYS     SYS     SYS     SYS
NIC3    SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS     PXB      X      SYS     SYS     SYS     SYS     SYS     SYS
NIC4    SYS     SYS     SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS      X      PXB     SYS     SYS     SYS     SYS
NIC5    SYS     SYS     SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS     PXB      X      SYS     SYS     SYS     SYS
NIC6    SYS     SYS     SYS     SYS     SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS      X      PXB     SYS     SYS
NIC7    SYS     SYS     SYS     SYS     SYS     SYS     PXB     PXB     SYS     SYS     SYS     SYS     SYS     SYS     PXB      X      SYS     SYS
NIC8    SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS      X      PIX
NIC9    SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     SYS     PIX      X 

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

NIC Legend:

  NIC0: mlx5_0
  NIC1: mlx5_1
  NIC2: mlx5_2
  NIC3: mlx5_3
  NIC4: mlx5_4
  NIC5: mlx5_5
  NIC6: mlx5_6
  NIC7: mlx5_7
  NIC8: mlx5_8
  NIC9: mlx5_9

🐛 Describe the bug

Phi-3 still seems to not be supported after latest vllm install.

model_id = "microsoft/Phi-3-mini-4k-instruct"
llm = LLM(model=model_id, trust_remote_code=True)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[5], line 11
---> 11 llm = LLM(model=model_id, trust_remote_code=True)
File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/entrypoints/llm.py:118, in LLM.__init__(self, model, tokenizer, tokenizer_mode, skip_tokenizer_init, trust_remote_code, tensor_parallel_size, dtype, quantization, revision, tokenizer_revision, seed, gpu_memory_utilization, swap_space, enforce_eager, max_context_len_to_capture, disable_custom_all_reduce, **kwargs)
     98     kwargs["disable_log_stats"] = True
     99 engine_args = EngineArgs(
    100     model=model,
    101     tokenizer=tokenizer,
   (...)
    116     **kwargs,
    117 )
--> 118 self.llm_engine = LLMEngine.from_engine_args(
    119     engine_args, usage_context=UsageContext.LLM_CLASS)
    120 self.request_counter = Counter()

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/engine/llm_engine.py:277, in LLMEngine.from_engine_args(cls, engine_args, usage_context)
    274     executor_class = GPUExecutor
    276 # Create the LLM engine.
--> 277 engine = cls(
    278     **engine_config.to_dict(),
    279     executor_class=executor_class,
    280     log_stats=not engine_args.disable_log_stats,
    281     usage_context=usage_context,
    282 )
    283 return engine

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/engine/llm_engine.py:148, in LLMEngine.__init__(self, model_config, cache_config, parallel_config, scheduler_config, device_config, load_config, lora_config, vision_language_config, speculative_config, decoding_config, executor_class, log_stats, usage_context)
    144 self.seq_counter = Counter()
    145 self.generation_config_fields = _load_generation_config_dict(
    146     model_config)
--> 148 self.model_executor = executor_class(
    149     model_config=model_config,
    150     cache_config=cache_config,
    151     parallel_config=parallel_config,
    152     scheduler_config=scheduler_config,
    153     device_config=device_config,
    154     lora_config=lora_config,
    155     vision_language_config=vision_language_config,
    156     speculative_config=speculative_config,
    157     load_config=load_config,
    158 )
    160 self._initialize_kv_caches()
    162 # If usage stat is enabled, collect relevant info.

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/executor/executor_base.py:41, in ExecutorBase.__init__(self, model_config, cache_config, parallel_config, scheduler_config, device_config, load_config, lora_config, vision_language_config, speculative_config)
     38 self.vision_language_config = vision_language_config
     39 self.speculative_config = speculative_config
---> 41 self._init_executor()

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/executor/gpu_executor.py:22, in GPUExecutor._init_executor(self)
     16 """Initialize the worker and load the model.
     17 
     18 If speculative decoding is enabled, we instead create the speculative
     19 worker.
     20 """
     21 if self.speculative_config is None:
---> 22     self._init_non_spec_worker()
     23 else:
     24     self._init_spec_worker()

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/executor/gpu_executor.py:51, in GPUExecutor._init_non_spec_worker(self)
     36 self.driver_worker = Worker(
     37     model_config=self.model_config,
     38     parallel_config=self.parallel_config,
   (...)
     48     is_driver_worker=True,
     49 )
     50 self.driver_worker.init_device()
---> 51 self.driver_worker.load_model()

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/worker/worker.py:117, in Worker.load_model(self)
    116 def load_model(self):
--> 117     self.model_runner.load_model()

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/worker/model_runner.py:162, in ModelRunner.load_model(self)
    160 def load_model(self) -> None:
    161     with CudaMemoryProfiler() as m:
--> 162         self.model = get_model(
    163             model_config=self.model_config,
    164             device_config=self.device_config,
    165             load_config=self.load_config,
    166             lora_config=self.lora_config,
    167             vision_language_config=self.vision_language_config,
    168             parallel_config=self.parallel_config,
    169             scheduler_config=self.scheduler_config,
    170         )
    172     self.model_memory_usage = m.consumed_memory
    173     logger.info(f"Loading model weights took "
    174                 f"{self.model_memory_usage / float(2**30):.4f} GB")

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/model_executor/model_loader/__init__.py:19, in get_model(model_config, load_config, device_config, parallel_config, scheduler_config, lora_config, vision_language_config)
     13 def get_model(
     14         *, model_config: ModelConfig, load_config: LoadConfig,
     15         device_config: DeviceConfig, parallel_config: ParallelConfig,
     16         scheduler_config: SchedulerConfig, lora_config: Optional[LoRAConfig],
     17         vision_language_config: Optional[VisionLanguageConfig]) -> nn.Module:
     18     loader = get_model_loader(load_config)
---> 19     return loader.load_model(model_config=model_config,
     20                              device_config=device_config,
     21                              lora_config=lora_config,
     22                              vision_language_config=vision_language_config,
     23                              parallel_config=parallel_config,
     24                              scheduler_config=scheduler_config)

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/model_executor/model_loader/loader.py:222, in DefaultModelLoader.load_model(self, model_config, device_config, lora_config, vision_language_config, parallel_config, scheduler_config)
    220 with set_default_torch_dtype(model_config.dtype):
    221     with torch.device(device_config.device):
--> 222         model = _initialize_model(model_config, self.load_config,
    223                                   lora_config, vision_language_config)
    224     model.load_weights(
    225         self._get_weights_iterator(model_config.model,
    226                                    model_config.revision,
   (...)
    229                                        "fall_back_to_pt_during_load",
    230                                        True)), )
    231     for _, module in model.named_modules():

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/model_executor/model_loader/loader.py:87, in _initialize_model(model_config, load_config, lora_config, vision_language_config)
     82 def _initialize_model(
     83         model_config: ModelConfig, load_config: LoadConfig,
     84         lora_config: Optional[LoRAConfig],
     85         vision_language_config: Optional[VisionLanguageConfig]) -> nn.Module:
     86     """Initialize a model with the given configurations."""
---> 87     model_class = get_model_architecture(model_config)[0]
     88     linear_method = _get_linear_method(model_config, load_config)
     90     return model_class(config=model_config.hf_config,
     91                        linear_method=linear_method,
     92                        **_get_model_initialization_kwargs(
     93                            model_class, lora_config, vision_language_config))

File ~/miniconda3/envs/vllm/lib/python3.10/site-packages/vllm/model_executor/model_loader/utils.py:35, in get_model_architecture(model_config)
     33     if model_cls is not None:
     34         return (model_cls, arch)
---> 35 raise ValueError(
     36     f"Model architectures {architectures} are not supported for now. "
     37     f"Supported architectures: {ModelRegistry.get_supported_archs()}")

ValueError: Model architectures ['Phi3ForCausalLM'] are not supported for now.

[jeejeelee]

The release version 0.4.1 does not yet support Phi3. You can build the source from the main branch, which does support Phi3.

[volkancirik]

When do you plan to release 0.4.1.post with official phi3 support?

Also, thanks a lot for the amazing work you’ve been doing!

[kevaldekivadiya2415]

+1

[ilkersigirci]

Phi-3 still not supported in the main branch even though #4298 is merged. Will there be any estimate about official release date? Thanks

[dxv2k]

+1

[JPonsa]

+1

[joshib123]

+1

[xingchaozh]

+1, Phi-3 still not supported in the main branch even though #4298 is merged

[shuxiaobo]

+1，still bugs in phi-3, which generation will not stop

[RasoulNik]

I cannot run Phi-3 with the vllm/vllm-openai:v0.4.2 image. I am using this command:

docker run -it --runtime nvidia --gpus all \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HUGGING_FACE_HUB_TOKEN=<secret>" \
    -p 8081:8000 \
    --ipc=host \
    --name vllm-openai-phi3 \
    vllm/vllm-openai:v0.4.2 \
    --model microsoft/Phi-3-mini-128k-instruct \
    --max-model-len 128000 \
    --dtype float16

I have tried to build the image from the source (main branch), but it takes a long time (45 minutes and still not finished).

[DarkLight1337]

Are you still encountering this issue in the latest version?

[RasoulNik]

In my setup, vllm/vllm-openai:v0.4.3 does not work at all, let alone phi3 :(

nvidia-smi
Fri Jun 14 07:06:10 2024       
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.171.04             Driver Version: 535.171.04   CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce RTX 3090        Off | 00000000:06:00.0 Off |                  N/A |
| 54%   23C    P8              12W / 350W |      3MiB / 24576MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   1  NVIDIA GeForce RTX 3090        Off | 00000000:07:00.0 Off |                  N/A |
| 54%   22C    P8              13W / 350W |      3MiB / 24576MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
                                                                                         
+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|  No running processes found                                                           |
+---------------------------------------------------------------------------------------+

Logs

docker compose up
WARN[0000] Found orphan containers ([backend-vllm-openai-phi3-1]) for this project. If you removed or renamed this service in your compose file, you can run this command with the --remove-orphans flag to clean it up. 
[+] Running 2/2
 ✔ Network backend_default          Created                                                                                                                                                             0.1s 
 ✔ Container backend-vllm-openai-1  Created                                                                                                                                                             0.1s 
Attaching to backend-vllm-openai-1
backend-vllm-openai-1  | /usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
backend-vllm-openai-1  |   warnings.warn(
backend-vllm-openai-1  | WARNING 06-14 07:04:02 config.py:1155] Casting torch.bfloat16 to torch.float16.
backend-vllm-openai-1  | 2024-06-14 07:04:06,104        INFO worker.py:1749 -- Started a local Ray instance.
backend-vllm-openai-1  | INFO 06-14 07:04:07 llm_engine.py:161] Initializing an LLM engine (v0.4.3) with config: model='cognitivecomputations/dolphin-2.9-llama3-8b', speculative_config=None, tokenizer='cognitivecomputations/dolphin-2.9-llama3-8b', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, rope_scaling=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=8000, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=2, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, quantization_param_path=None, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='outlines'), seed=0, served_model_name=cognitivecomputations/dolphin-2.9-llama3-8b)
backend-vllm-openai-1  | Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148] Error executing method init_worker. This might cause deadlock in distributed execution.
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148] Traceback (most recent call last):
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 140, in execute_method
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]     return executor(*args, **kwargs)
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 134, in init_worker
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]     self.worker = worker_class(*args, **kwargs)
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker.py", line 74, in __init__
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]     self.model_runner = ModelRunnerClass(
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/model_runner.py", line 115, in __init__
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]     self.attn_backend = get_attn_backend(
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/attention/selector.py", line 43, in get_attn_backend
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]     backend = which_attn_to_use(num_heads, head_size, num_kv_heads,
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/attention/selector.py", line 118, in which_attn_to_use
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]     if torch.cuda.get_device_capability()[0] < 8:
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py", line 430, in get_device_capability
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]     prop = get_device_properties(device)
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py", line 444, in get_device_properties
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]     _lazy_init()  # will define _get_device_properties
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py", line 293, in _lazy_init
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148]     torch._C._cuda_init()
backend-vllm-openai-1  | ERROR 06-14 07:04:12 worker_base.py:148] RuntimeError: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 804: forward compatibility was attempted on non supported HW
backend-vllm-openai-1  | Traceback (most recent call last):
backend-vllm-openai-1  |   File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
backend-vllm-openai-1  |     return _run_code(code, main_globals, None,
backend-vllm-openai-1  |  

 File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
backend-vllm-openai-1  |     exec(code, run_globals)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/api_server.py", line 186, in <module>
backend-vllm-openai-1  |     engine = AsyncLLMEngine.from_engine_args(
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 386, in from_engine_args
backend-vllm-openai-1  |     engine = cls(
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 340, in __init__
backend-vllm-openai-1  |     self.engine = self._init_engine(*args, **kwargs)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 462, in _init_engine
backend-vllm-openai-1  |     return engine_class(*args, **kwargs)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/llm_engine.py", line 222, in __init__
backend-vllm-openai-1  |     self.model_executor = executor_class(
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/executor/ray_gpu_executor.py", line 317, in __init__
backend-vllm-openai-1  |     super().__init__(*args, **kwargs)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/executor/distributed_gpu_executor.py", line 25, in __init__
backend-vllm-openai-1  |     super().__init__(*args, **kwargs)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/executor/executor_base.py", line 41, in __init__
backend-vllm-openai-1  |     self._init_executor()
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/executor/ray_gpu_executor.py", line 40, in _init_executor
backend-vllm-openai-1  |     self._init_workers_ray(placement_group)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/executor/ray_gpu_executor.py", line 169, in _init_workers_ray
backend-vllm-openai-1  |     self._run_workers("init_worker", all_kwargs=init_worker_all_kwargs)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/executor/ray_gpu_executor.py", line 246, in _run_workers
backend-vllm-openai-1  |     driver_worker_output = self.driver_worker.execute_method(
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 149, in execute_method
backend-vllm-openai-1  |     raise e
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 140, in execute_method
backend-vllm-openai-1  |     return executor(*args, **kwargs)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 134, in init_worker
backend-vllm-openai-1  |     self.worker = worker_class(*args, **kwargs)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker.py", line 74, in __init__
backend-vllm-openai-1  |     self.model_runner = ModelRunnerClass(
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/model_runner.py", line 115, in __init__
backend-vllm-openai-1  |     self.attn_backend = get_attn_backend(
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/attention/selector.py", line 43, in get_attn_backend
backend-vllm-openai-1  |     backend = which_attn_to_use(num_heads, head_size, num_kv_heads,
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/attention/selector.py", line 118, in which_attn_to_use
backend-vllm-openai-1  |     if torch.cuda.get_device_capability()[0] < 8:
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py", line 430, in get_device_capability
backend-vllm-openai-1  |     prop = get_device_properties(device)
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py", line 444, in get_device_properties
backend-vllm-openai-1  |     _lazy_init()  # will define _get_device_properties
backend-vllm-openai-1  |   File "/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py", line 293, in _lazy_init
backend-vllm-openai-1  |     torch._C._cuda_init()
backend-vllm-openai-1  | RuntimeError: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 804: forward compatibility was attempted on non supported HW
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148] Error executing method init_worker. This might cause deadlock in distributed execution.
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148] Traceback (most recent call last):
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 140, in execute_method
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     return executor(*args, **kwargs)
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/ray/util/tracing/tracing_helper.py", line 467, in _resume_span
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     return method(self, *_args, **_kwargs)
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 134, in init_worker
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     self.worker = worker_class(*args, **kwargs)
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker.py", line 74, in __init__
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     self.model_runner = ModelRunnerClass(
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/model_runner.py", line 115, in __init__
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     self.att

n_backend = get_attn_backend(
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/attention/selector.py", line 43, in get_attn_backend
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     backend = which_attn_to_use(num_heads, head_size, num_kv_heads,
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/vllm/attention/selector.py", line 118, in which_attn_to_use
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     if torch.cuda.get_device_capability()[0] < 8:
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py", line 430, in get_device_capability
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     prop = get_device_properties(device)
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py", line 444, in get_device_properties
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     _lazy_init()  # will define _get_device_properties
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]   File "/usr/local/lib/python3.10/dist-packages/torch/cuda/__init__.py", line 293, in _lazy_init
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148]     torch._C._cuda_init()
backend-vllm-openai-1  | (RayWorkerWrapper pid=643) ERROR 06-14 07:04:12 worker_base.py:148] RuntimeError: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 804: forward compatibility was attempted on non supported HW
backend-vllm-openai-1 exited with code 1

[DarkLight1337]

Can you try installing the latest vLLM version (0.5.0.post1)?

[youkaichao]

@RasoulNik your issue is a driver issue. see #4940 (comment)