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vllm-project / vllm

A high-throughput and memory-efficient inference and serving engine for LLMs
https://docs.vllm.ai
Apache License 2.0
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[Usage]: When I installed vllm version 0.5.3.post1, there was a problem deploying qwen2 #7295

Closed Uhao-P closed 1 month ago

Uhao-P commented 1 month ago

Your current environment

The output of `python collect_env.py`

Collecting environment information... PyTorch version: 2.3.1+cu121 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64) GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 Clang version: Could not collect CMake version: version 3.30.1 Libc version: glibc-2.31

Python version: 3.10.14 (main, May 6 2024, 19:42:50) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-5.15.0-78-generic-x86_64-with-glibc2.31 Is CUDA available: True CUDA runtime version: 12.1.105 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: Quadro RTX 8000 GPU 1: Quadro RTX 8000 GPU 2: Quadro RTX 8000 GPU 3: Quadro RTX 8000 GPU 4: Quadro RTX 8000 GPU 5: Quadro RTX 8000 GPU 6: Quadro RTX 8000 GPU 7: Quadro RTX 8000

Nvidia driver version: 535.183.01 cuDNN version: Probably one of the following: /usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.0 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 Byte Order: Little Endian Address sizes: 46 bits physical, 48 bits virtual CPU(s): 64 On-line CPU(s) list: 0-31 Off-line CPU(s) list: 32-63 Thread(s) per core: 1 Core(s) per socket: 16 Socket(s): 2 NUMA node(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 79 Model name: Intel(R) Xeon(R) CPU E5-2683 v4 @ 2.10GHz Stepping: 1 CPU MHz: 1200.000 CPU max MHz: 3000.0000 CPU min MHz: 1200.0000 BogoMIPS: 4201.69 Virtualization: VT-x L1d cache: 512 KiB L1i cache: 512 KiB L2 cache: 4 MiB L3 cache: 40 MiB NUMA node0 CPU(s): 0-15,32-47 NUMA node1 CPU(s): 16-31,48-63 Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled Vulnerability L1tf: Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable Vulnerability Mds: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Meltdown: Mitigation; PTI Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Retbleed: Not affected 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, IBRS_FW, STIBP conditional, RSB filling, PBRSB-eIBRS Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; Clear CPU buffers; SMT vulnerable Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdt_a rdseed adx smap intel_pt xsaveopt cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts md_clear flush_l1d

Versions of relevant libraries: [pip3] numpy==1.26.4 [pip3] nvidia-nccl-cu12==2.20.5 [pip3] onnx==1.16.2 [pip3] onnxruntime==1.18.1 [pip3] pyzmq==26.0.3 [pip3] torch==2.3.1+cu121 [pip3] torch-tb-profiler==0.4.3 [pip3] torchaudio==2.3.1+cu121 [pip3] torchvision==0.18.1+cu121 [pip3] transformers==4.43.3 [pip3] triton==2.3.1 [conda] numpy 1.26.4 py310hb13e2d6_0 conda-forge [conda] nvidia-nccl-cu12 2.20.5 pypi_0 pypi [conda] pyzmq 26.0.3 pypi_0 pypi [conda] torch 2.3.1+cu121 pypi_0 pypi [conda] torch-tb-profiler 0.4.3 pypi_0 pypi [conda] torchaudio 2.3.1+cu121 pypi_0 pypi [conda] torchvision 0.18.1+cu121 pypi_0 pypi [conda] transformers 4.43.3 pypi_0 pypi [conda] triton 2.3.1 pypi_0 pypi ROCM Version: Could not collect Neuron SDK Version: N/A vLLM Version: 0.5.3.post1 vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled GPU Topology: GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 NIC1 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X NV2 PIX PIX PHB PHB PHB PHB PHB PHB 0 N/A GPU1 NV2 X PIX PIX PHB PHB PHB PHB PHB PHB 0 N/A GPU2 PIX PIX X NV2 PHB PHB PHB PHB PHB PHB 0 N/A GPU3 PIX PIX NV2 X PHB PHB PHB PHB PHB PHB 0 N/A GPU4 PHB PHB PHB PHB X PIX PIX PIX PHB PHB 0 N/A GPU5 PHB PHB PHB PHB PIX X PIX NV2 PHB PHB 0 N/A GPU6 PHB PHB PHB PHB PIX PIX X PIX PHB PHB 0 N/A GPU7 PHB PHB PHB PHB PIX NV2 PIX X PHB PHB 0 N/A NIC0 PHB PHB PHB PHB PHB PHB PHB PHB X PIX NIC1 PHB PHB PHB PHB PHB PHB PHB PHB 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

How would you like to use vllm

start vllm

python3 -m vllm.entrypoints.openai.api_server --model /input0/ --host 0.0.0.0 --port 8888 --worker-use-ray --max-num-seqs 256 --tensor-parallel-size 8 --dtype half --rope-scaling '{"type":"dynamic","factor":4.0}'

Calling interface

curl http://localhost: 8888/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
    "model": "/input0/",
    "max_tokens": 1024,
    "stream": false,
    "messages": [
        {"role": "user", "content": "你是谁？"}
    ]
}'

Interface return

{"id":"chat-23a35aa9f1ee438e93dae044a557df2f","object":"chat.completion","created":1723094866,"model":"/input1/","choices":[{"index":0,"message":{"role":"assistant","content":" Help HELP HELP HELP HELP HELP.HELP 1 1 1 0 1 m tr 0 0 0 0 0 1 1 0 0 1 1 0 1  are 1 1 1 0                 HELP  HELP                         a              |0                     =          HELP    |   0  HELP   v     ')      ')         r    r               (  ')               I,      r   \n\n          HELP        .  of          \n\n            have         HELP       ?          help      help       ')            r      .f    \n\n      be  .           |   ')\n .  .              and   .               .    . .       the       ,     ,     .    and              \n\n ,    HELP             \n\n     .\n\n      l ;                             \n             \n\n         hat  at      r                   1    ?     HELP   r            \n\n    r  .        r                \n  that |  , \n\n     help   ;                .  .                  for  .   .                  have.',             not             \n\n    ',    \n       1  are    \n\n      ..      ;         ;                |                   .      ||       you   '               ?                                               \n       |          which    \n\n          and   i     ',        HELP      ;                  help       M   0        I                  |        ","tool_calls":[]},"logprobs":null,"finish_reason":"length","stop_reason":null}],"usage":{"prompt_tokens":22,"total_tokens":1046,"completion_tokens":1024}}
Uhao-P commented 1 month ago

I uninstalled vllm and reinstalled the same version and found that the service was normal