Skip to content

[Installation]: installation broken after #17259 #17360

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
1 task done
hhy3 opened this issue Apr 29, 2025 · 6 comments
Closed
1 task done

[Installation]: installation broken after #17259 #17360

hhy3 opened this issue Apr 29, 2025 · 6 comments
Labels
installation Installation problems

Comments

@hhy3
Copy link
Contributor

hhy3 commented Apr 29, 2025

Your current environment

The output of `python collect_env.py`
PyTorch version: 2.8.0a0+git414ce71
Is debug build: False
CUDA used to build PyTorch: 12.8
ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04.1 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version: 18.1.3 (1ubuntu1)
CMake version: version 4.0.0
Libc version: glibc-2.39

Python version: 3.12.0 | packaged by Anaconda, Inc. | (main, Oct  2 2023, 17:29:18) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.167.4-microsoft-standard-WSL2-x86_64-with-glibc2.39
Is CUDA available: True
CUDA runtime version: 12.8.61
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 5080
Nvidia driver version: 572.42
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.7.1
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):                               16
On-line CPU(s) list:                  0-15
Vendor ID:                            AuthenticAMD
Model name:                           AMD Ryzen 7 9800X3D 8-Core Processor
CPU family:                           26
Model:                                68
Thread(s) per core:                   2
Core(s) per socket:                   8
Socket(s):                            1
Stepping:                             0
BogoMIPS:                             9399.80
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 pni pclmulqdq ssse3 fma cx16 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 perfctr_core ssbd ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx_vnni avx512_bf16 clzero xsaveerptr arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload avx512vbmi umip avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid fsrm avx512_vp2intersect
Virtualization:                       AMD-V
Hypervisor vendor:                    Microsoft
Virtualization type:                  full
L1d cache:                            384 KiB (8 instances)
L1i cache:                            256 KiB (8 instances)
L2 cache:                             8 MiB (8 instances)
L3 cache:                             96 MiB (1 instance)
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:               Not affected
Vulnerability Spec rstack overflow:   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 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] mypy==1.10.1
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.0
[pip3] pyzmq==26.4.0
[pip3] torch==2.8.0a0+git414ce71
[pip3] torchaudio==2.6.0
[pip3] torchaudio==2.6.0
[pip3] torchvision==0.22.0a0+f799a53
[pip3] transformers==4.51.3
[pip3] triton==3.3.0
[conda] numpy                     1.26.0                   pypi_0    pypi
[conda] pyzmq                     26.4.0                   pypi_0    pypi
[conda] torch                     2.8.0a0+git414ce71          pypi_0    pypi
[conda] torchaudio                2.6.0                    pypi_0    pypi
[conda] torchvision               0.22.0a0+f799a53           dev_0    <develop>
[conda] transformers              4.51.3                   pypi_0    pypi
[conda] triton                    3.3.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.1.dev1363+g2c89cd9.d20250429 (git sha: 2c89cd9, date: 20250429)
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
        GPU0    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X                              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

NCCL_CUMEM_ENABLE=0
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY

How you are installing vllm

python use_existing_torch.py
python setup.py develop -i https://pypi.tuna.tsinghua.edu.cn -v

It says

configuration error: `project.license` must be valid exactly by one definition (2 matches found):

    - keys:
        'file': {type: string}
      required: ['file']
    - keys:
        'text': {type: string}
      required: ['text']

DESCRIPTION:
    `Project license <https://peps.python.org/pep-0621/#license>`_.

GIVEN VALUE:
    "Apache-2.0"

OFFENDING RULE: 'oneOf'

DEFINITION:
    {
        "oneOf": [
            {
                "properties": {
                    "file": {
                        "type": "string",
                        "$$description": [
                            "Relative path to the file (UTF-8) which contains the license for the",
                            "project."
                        ]
                    }
                },
                "required": [
                    "file"
                ]
            },
            {
                "properties": {
                    "text": {
                        "type": "string",
                        "$$description": [
                            "The license of the project whose meaning is that of the",
                            "`License field from the core metadata",
                            "<https://packaging.python.org/specifications/core-metadata/#license>`_."
                        ]
                    }
                },
                "required": [
                    "text"
                ]
            }
        ]
    }

Before submitting a new issue...

  • Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.
@hhy3 hhy3 added the installation Installation problems label Apr 29, 2025
@zhaoyinglia
Copy link

same error!

@hackey
Copy link

hackey commented Apr 29, 2025

Here's a solution for those who build from dockerfile:
Need to replace in pyproject.toml file
[project]
name = "vllm"
authors = [{name = "vLLM Team"}]
license = "Apache-2.0"
license-files = ["LICENSE"]
readme = "README.md"

To this:
[project]
name = "vllm"
authors = [{name = "vLLM Team"}]
license = {text = "Apache-2.0"}
readme = "README.md"

What surprises me most is how such bugs are merged into branches and releases. Do you have DevOps and test coverage?

@g0t4
Copy link

g0t4 commented Apr 30, 2025

Also can use this to fix the build, edit pyproject.toml and remove the license and license-files and add back:

license = { "file"= "LICENSE" }

@ttio2tech
Copy link

just need to remove the line 18, 19 in the pyproject.toml:
license = "Apache-2.0"
license-files = ["LICENSE"]

I suspect it's AI added outdated code.

@DarkLight1337
Copy link
Member

This is an intentional change. See #17259

@DarkLight1337
Copy link
Member

Closing as fixed by #17389. You just have to update setuptools

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
installation Installation problems
Projects
None yet
Development

No branches or pull requests

6 participants