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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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[Installation]: Build vllm environment error #10303

Open Kawai1Ace opened 1 week ago

Kawai1Ace commented 1 week ago

Your current environment

WARNING 11-14 02:19:07 _custom_ops.py:20] Failed to import from vllm._C with ModuleNotFoundError("No module named 'vllm._C'")
Collecting environment information...
PyTorch version: 2.4.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.3 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04) 9.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.31

Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.11.0-40-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 12.6.77
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA GeForce RTX 3090
GPU 1: NVIDIA GeForce RTX 3090
GPU 2: NVIDIA GeForce RTX 3090
GPU 3: NVIDIA GeForce RTX 3090
GPU 4: NVIDIA GeForce RTX 3090
GPU 5: NVIDIA GeForce RTX 3090
GPU 6: NVIDIA GeForce RTX 3090
GPU 7: NVIDIA GeForce RTX 3090

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
Byte Order:                      Little Endian
Address sizes:                   46 bits physical, 48 bits virtual
CPU(s):                          64
On-line CPU(s) list:             0-63
Thread(s) per core:              2
Core(s) per socket:              16
Socket(s):                       2
NUMA node(s):                    2
Vendor ID:                       GenuineIntel
CPU family:                      6
Model:                           85
Model name:                      Intel(R) Xeon(R) Silver 4216 CPU @ 2.10GHz
Stepping:                        7
CPU MHz:                         833.694
CPU max MHz:                     3200.0000
CPU min MHz:                     800.0000
BogoMIPS:                        4200.00
Virtualization:                  VT-x
L1d cache:                       1 MiB
L1i cache:                       1 MiB
L2 cache:                        32 MiB
L3 cache:                        44 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:              Not affected
Vulnerability Mds:               Not affected
Vulnerability Meltdown:          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; Enhanced IBRS, IBPB conditional, RSB filling
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Mitigation; TSX disabled
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 art 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 intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities

Versions of relevant libraries:
[pip3] numpy==1.26.3
[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-nccl-cu12==2.20.5
[pip3] nvidia-nvjitlink-cu12==12.1.105
[pip3] nvidia-nvtx-cu12==12.1.105
[pip3] torch==2.4.0+cu121
[pip3] torchaudio==2.4.0+cu121
[pip3] torchvision==0.19.0+cu121
[pip3] transformers==4.46.2
[pip3] triton==3.0.0
[conda] cuda-cccl_linux-64        12.6.77                       0    nvidia
[conda] cuda-compiler             12.6.2                        0    nvidia
[conda] cuda-crt-dev_linux-64     12.6.77                       0    nvidia
[conda] cuda-crt-tools            12.6.77                       0    nvidia
[conda] cuda-cudart               12.6.77                       0    nvidia
[conda] cuda-cudart-dev           12.6.77                       0    nvidia
[conda] cuda-cudart-dev_linux-64  12.6.77                       0    nvidia
[conda] cuda-cudart-static        12.6.77                       0    nvidia
[conda] cuda-cudart-static_linux-64 12.6.77                       0    nvidia
[conda] cuda-cudart_linux-64      12.6.77                       0    nvidia
[conda] cuda-cuobjdump            12.6.77                       0    nvidia
[conda] cuda-cuxxfilt             12.6.77                       0    nvidia
[conda] cuda-driver-dev_linux-64  12.6.77                       0    nvidia
[conda] cuda-nvcc                 12.6.77                       0    nvidia
[conda] cuda-nvcc-dev_linux-64    12.6.77                       0    nvidia
[conda] cuda-nvcc-impl            12.6.77                       0    nvidia
[conda] cuda-nvcc-tools           12.6.77                       0    nvidia
[conda] cuda-nvcc_linux-64        12.6.77                       0    nvidia
[conda] cuda-nvdisasm             12.6.77                       0    nvidia
[conda] cuda-nvprune              12.6.77                       0    nvidia
[conda] cuda-nvvm-dev_linux-64    12.6.77                       0    nvidia
[conda] cuda-nvvm-impl            12.6.77                       0    nvidia
[conda] cuda-nvvm-tools           12.6.77                       0    nvidia
[conda] cuda-version              12.6                          3    nvidia
[conda] numpy                     1.26.3                   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-nccl-cu12          2.20.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.1.105                 pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.1.105                 pypi_0    pypi
[conda] torch                     2.4.0+cu121              pypi_0    pypi
[conda] torchaudio                2.4.0+cu121              pypi_0    pypi
[conda] torchvision               0.19.0+cu121             pypi_0    pypi
[conda] transformers              4.46.2                   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.post2.dev333+g19682023.d20241110
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      PIX     NODE    NODE    SYS     SYS     SYS     SYS     0-15,32-47      0               N/A
GPU1    PIX      X      NODE    NODE    SYS     SYS     SYS     SYS     0-15,32-47      0               N/A
GPU2    NODE    NODE     X      PIX     SYS     SYS     SYS     SYS     0-15,32-47      0               N/A
GPU3    NODE    NODE    PIX      X      SYS     SYS     SYS     SYS     0-15,32-47      0               N/A
GPU4    SYS     SYS     SYS     SYS      X      PIX     NODE    NODE    16-31,48-63     1               N/A
GPU5    SYS     SYS     SYS     SYS     PIX      X      NODE    NODE    16-31,48-63     1               N/A
GPU6    SYS     SYS     SYS     SYS     NODE    NODE     X      PIX     16-31,48-63     1               N/A
GPU7    SYS     SYS     SYS     SYS     NODE    NODE    PIX      X      16-31,48-63     1               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

CUDA_MODULE_LOADING=LAZY

How you are installing vllm

git clone https://github.com/vllm-project/vllm.git
cd vllm
pip install -e .

图片

Before submitting a new issue...

AaronWang04 commented 1 week ago

did you try and set MAX_JOBS=6? also I would suggest try running pip in verbose mode with -vvv to see more fine outputs