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[Bug]: Unable to configure formatter 'vllm' #10457

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pspdada opened this issue Nov 19, 2024 · 2 comments · May be fixed by #10458
Open
1 task done

[Bug]: Unable to configure formatter 'vllm' #10457

pspdada opened this issue Nov 19, 2024 · 2 comments · May be fixed by #10458
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@pspdada
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pspdada commented Nov 19, 2024

Your current environment

The output of `python collect_env.py`
PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
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 3.30.2
Libc version: glibc-2.35

Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-120-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A100-PCIE-40GB
GPU 1: NVIDIA A100-PCIE-40GB

Nvidia driver version: 550.107.02
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.7
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:                        40 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               8
On-line CPU(s) list:                  0-7
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Silver 4316 CPU @ 2.30GHz
CPU family:                           6
Model:                                106
Thread(s) per core:                   1
Core(s) per socket:                   8
Socket(s):                            1
Stepping:                             6
BogoMIPS:                             4589.21
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology cpuid pni pclmulqdq vmx ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch topoext cpuid_fault invpcid_single pti ssbd ibrs ibpb tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid
Virtualization:                       VT-x
L1d cache:                            256 KiB (8 instances)
L1i cache:                            256 KiB (8 instances)
L2 cache:                             32 MiB (8 instances)
L3 cache:                             16 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-7
Vulnerability Gather data sampling:   Unknown: Dependent on hypervisor status
Vulnerability Itlb multihit:          KVM: Mitigation: VMX disabled
Vulnerability L1tf:                   Mitigation; PTE Inversion; VMX conditional cache flushes, SMT disabled
Vulnerability Mds:                    Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Meltdown:               Mitigation; PTI
Vulnerability Mmio stale data:        Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
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 disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Retpoline
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] curated-transformers==0.1.1
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-ml-py==12.560.30
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pyzmq==26.2.0
[pip3] sentence-transformers==3.2.1
[pip3] spacy-curated-transformers==0.3.0
[pip3] torch==2.5.1
[pip3] torchaudio==2.5.1
[pip3] torchscale==0.3.0
[pip3] torchvision==0.20.1
[pip3] transformers==4.46.2
[pip3] triton==3.1.0
[conda] curated-transformers      0.1.1                    pypi_0    pypi
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] nvidia-cublas-cu12        12.4.5.8                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.4.127                 pypi_0    pypi
[conda] nvidia-cudnn-cu12         9.1.0.70                 pypi_0    pypi
[conda] nvidia-cufft-cu12         11.2.1.3                 pypi_0    pypi
[conda] nvidia-curand-cu12        10.3.5.147               pypi_0    pypi
[conda] nvidia-cusolver-cu12      11.6.1.9                 pypi_0    pypi
[conda] nvidia-cusparse-cu12      12.3.1.170               pypi_0    pypi
[conda] nvidia-ml-py              12.560.30                pypi_0    pypi
[conda] nvidia-nccl-cu12          2.21.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.4.127                 pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.4.127                 pypi_0    pypi
[conda] pyzmq                     26.2.0                   pypi_0    pypi
[conda] sentence-transformers     3.2.1                    pypi_0    pypi
[conda] spacy-curated-transformers 0.3.0                    pypi_0    pypi
[conda] torch                     2.5.1                    pypi_0    pypi
[conda] torchaudio                2.5.1                    pypi_0    pypi
[conda] torchscale                0.3.0                    pypi_0    pypi
[conda] torchvision               0.20.1                   pypi_0    pypi
[conda] transformers              4.46.2                   pypi_0    pypi
[conda] triton                    3.1.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.4.post1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    GPU1    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      PHB     0-7     0               N/A
GPU1    PHB      X      0-7     0               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_HOME=/usr/local/cuda-12.4
CUDA_HOME=/usr/local/cuda-12.4
LD_LIBRARY_PATH=/root/anaconda3/envs/LVLM/lib/python3.10/site-packages/cv2/../../lib64::/usr/local/cuda-12.4/lib64
CUDA_MODULE_LOADING=LAZY

Model Input Dumps

🐛 Describe the bug

Raise ValueError: Unable to configure formatter 'vllm' when using the latest version of vllm, using the previous verson don't break anything. Rolling back the vllm version to 0.6.2 resolves the issue.
The content of vllm_logging_config.json can be found in https://github.com/vllm-project/vllm/blob/main/examples/logging_configuration.md
The content is:

{
  "formatters": {
    "vllm": {
      "class": "vllm.logging.NewLineFormatter",
      "datefmt": "%m-%d %H:%M:%S",
      "format": "%(levelname)s %(asctime)s %(filename)s:%(lineno)d] %(message)s"
    }
  },
  "handlers": {
    "vllm": {
      "class" : "logging.StreamHandler",
      "formatter": "vllm",
      "level": "INFO",
      "stream": "ext://sys.stdout"
    }
  },
  "loggers": {
    "vllm": {
      "handlers": ["vllm"],
      "level": "DEBUG",
      "propagage": false
    },
    "vllm.example_noisy_logger": {
      "propagate": false
    }
  },
  "version": 1
}

The related content in .env file:

VLLM_CONFIGURE_LOGGING=1
VLLM_LOGGING_CONFIG_PATH="./utils/vllm_logging_config.json"

The error:

  File "/root/llm-project/LVLM/model/blip2.py", line 12, in <module>
    from vllm import LLM
  File "/root/anaconda3/envs/LVLM/lib/python3.10/site-packages/vllm/__init__.py", line 3, in <module>
    from vllm.engine.arg_utils import AsyncEngineArgs, EngineArgs
  File "/root/anaconda3/envs/LVLM/lib/python3.10/site-packages/vllm/engine/arg_utils.py", line 11, in <module>
    from vllm.config import (CacheConfig, ConfigFormat, DecodingConfig,
  File "/root/anaconda3/envs/LVLM/lib/python3.10/site-packages/vllm/config.py", line 13, in <module>
    from vllm.logger import init_logger
  File "/root/anaconda3/envs/LVLM/lib/python3.10/site-packages/vllm/logger.py", line 93, in <module>
    _configure_vllm_root_logger()
  File "/root/anaconda3/envs/LVLM/lib/python3.10/site-packages/vllm/logger.py", line 79, in _configure_vllm_root_logger
    dictConfig(logging_config)
  File "/root/anaconda3/envs/LVLM/lib/python3.10/logging/config.py", line 811, in dictConfig
    dictConfigClass(config).configure()
  File "/root/anaconda3/envs/LVLM/lib/python3.10/logging/config.py", line 547, in configure
    raise ValueError('Unable to configure '
ValueError: Unable to configure formatter 'vllm'

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@pspdada pspdada added the bug Something isn't working label Nov 19, 2024
@russellb
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Thanks for the report! I'm looking into it.

@russellb
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This config was broken by #10134. I'll post a fix shortly.

@russellb russellb self-assigned this Nov 19, 2024
russellb added a commit to russellb/vllm that referenced this issue Nov 19, 2024
`logging_configuration.md` provides some sample logger configuration
that is no logner valid after vllm-project#10134. This PR fixes the sample config,
as well as provides backwards compatibility so that existing
configuration files won't break.

Closes vllm-project#10457

Signed-off-by: Russell Bryant <[email protected]>
@russellb russellb linked a pull request Nov 19, 2024 that will close this issue
russellb added a commit to russellb/vllm that referenced this issue Nov 21, 2024
`logging_configuration.md` provides some sample logger configuration
that is no logner valid after vllm-project#10134. This PR fixes the sample config,
as well as provides backwards compatibility so that existing
configuration files won't break.

Closes vllm-project#10457

Signed-off-by: Russell Bryant <[email protected]>
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