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[Bug]: Benchmark script - TypeError: argument 'text': 'list' object cannot be converted to 'PyString' #12144

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vijaypal89 opened this issue Jan 17, 2025 · 5 comments · Fixed by #12149
Closed
1 task done

[Bug]: Benchmark script - TypeError: argument 'text': 'list' object cannot be converted to 'PyString' #12144

vijaypal89 opened this issue Jan 17, 2025 · 5 comments · Fixed by #12149
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bug Something isn't working

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@vijaypal89
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Your current environment

The output of `python collect_env.py` 
RuntimeWarning: Failed to read commit hash:
No module named 'vllm._version'
  from vllm.version import __version__ as VLLM_VERSION
Collecting environment information...
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 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.11.10 (main, Oct  3 2024, 07:29:13) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-124-generic-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
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:                        46 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               16
On-line CPU(s) list:                  0-15
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Platinum 8358 CPU @ 2.60GHz
CPU family:                           15
Model:                                6
Thread(s) per core:                   1
Core(s) per socket:                   1
Socket(s):                            16
Stepping:                             1
BogoMIPS:                             5200.00
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss syscall nx pdpe1gb rdtscp lm constant_tsc nopl xtopology cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced 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 wbnoinvd arat avx512vbmi umip avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid fsrm md_clear arch_capabilities
Hypervisor vendor:                    KVM
Virtualization type:                  full
L1d cache:                            512 KiB (16 instances)
L1i cache:                            512 KiB (16 instances)
L2 cache:                             64 MiB (16 instances)
L3 cache:                             256 MiB (16 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-15
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:        Unknown: No mitigations
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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[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] torch==2.5.1
[pip3] torchvision==0.20.1
[pip3] transformers==4.45.2
[pip3] triton==3.1.0
[pip3] zmq==0.0.0
[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] torch                     2.5.1                    pypi_0    pypi
[conda] torchvision               0.20.1                   pypi_0    pypi
[conda] transformers              4.45.2                   pypi_0    pypi
[conda] triton                    3.1.0                    pypi_0    pypi
[conda] zmq                       0.0.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: N/A (dev)
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
Could not collect

LD_LIBRARY_PATH=/home/vijay/miniconda3/envs/nai/lib/python3.11/site-packages/cv2/../../lib64:

Model Input Dumps

vllm version 0.6.6
Running below command -

python3 benchmarks/benchmark_serving.py --backend openai-chat --model msnemo24072h100gv  --base-url <serving url> --dataset-name sonnet --dataset-path benchmarks/sonnet.txt --request-rate 16 --num-prompts 256 --endpoint /api/v1/chat/completions --sonnet-input-len=3864 --sonnet-output-len=200 --sonnet-prefix-len=3764 --tokenizer mistralai/Mistral-Nemo-Instruct-2407 --tokenizer-mode mistral

Getting below error

Traceback (most recent call last):
  File "/home/vijay/vllm/benchmarks/benchmark_serving.py", line 1226, in <module>
    main(args)
  File "/home/vijay/vllm/benchmarks/benchmark_serving.py", line 821, in main
    input_requests = sample_sonnet_requests(
                     ^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/vllm/benchmarks/benchmark_serving.py", line 149, in sample_sonnet_requests
    poem_token_ids = tokenizer(poem_lines).input_ids
                     ^^^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/miniconda3/envs/nai/lib/python3.11/site-packages/vllm/transformers_utils/tokenizers/mistral.py", line 232, in __call__
    input_ids = self.encode(prompt)
                ^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/miniconda3/envs/nai/lib/python3.11/site-packages/vllm/transformers_utils/tokenizers/mistral.py", line 252, in encode
    return self.tokenizer.encode(prompt, bos=True, eos=False)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/miniconda3/envs/nai/lib/python3.11/site-packages/mistral_common/tokens/tokenizers/tekken.py", line 220, in encode
    tokens: List[int] = self._model.encode(s)
                        ^^^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/miniconda3/envs/nai/lib/python3.11/site-packages/tiktoken/core.py", line 124, in encode
    return self._core_bpe.encode(text, allowed_special)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: argument 'text': 'list' object cannot be converted to 'PyString'

🐛 Describe the bug

vllm version 0.6.6
Running below command -

python3 benchmarks/benchmark_serving.py --backend openai-chat --model msnemo24072h100gv  --base-url <serving url> --dataset-name sonnet --dataset-path benchmarks/sonnet.txt --request-rate 16 --num-prompts 256 --endpoint /api/v1/chat/completions --sonnet-input-len=3864 --sonnet-output-len=200 --sonnet-prefix-len=3764 --tokenizer mistralai/Mistral-Nemo-Instruct-2407 --tokenizer-mode mistral

Getting below error

Traceback (most recent call last):
  File "/home/vijay/vllm/benchmarks/benchmark_serving.py", line 1226, in <module>
    main(args)
  File "/home/vijay/vllm/benchmarks/benchmark_serving.py", line 821, in main
    input_requests = sample_sonnet_requests(
                     ^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/vllm/benchmarks/benchmark_serving.py", line 149, in sample_sonnet_requests
    poem_token_ids = tokenizer(poem_lines).input_ids
                     ^^^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/miniconda3/envs/nai/lib/python3.11/site-packages/vllm/transformers_utils/tokenizers/mistral.py", line 232, in __call__
    input_ids = self.encode(prompt)
                ^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/miniconda3/envs/nai/lib/python3.11/site-packages/vllm/transformers_utils/tokenizers/mistral.py", line 252, in encode
    return self.tokenizer.encode(prompt, bos=True, eos=False)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/miniconda3/envs/nai/lib/python3.11/site-packages/mistral_common/tokens/tokenizers/tekken.py", line 220, in encode
    tokens: List[int] = self._model.encode(s)
                        ^^^^^^^^^^^^^^^^^^^^^
  File "/home/vijay/miniconda3/envs/nai/lib/python3.11/site-packages/tiktoken/core.py", line 124, in encode
    return self._core_bpe.encode(text, allowed_special)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: argument 'text': 'list' object cannot be converted to 'PyString'

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@vijaypal89 vijaypal89 added the bug Something isn't working label Jan 17, 2025
@jikunshang
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what's mistral_common and tiktoken version in your env? I tried mistral_common 1.5.1 and tiktoken 0.7.0 which cannot reproduce.

@vijaypal89
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@jikunshang I have exact same version mistral_common 1.5.1 and tiktoken 0.7.0

@vijaypal89
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@jikunshang Another thing to mention is that, this is happening only for few mistral models only.

@jikunshang jikunshang mentioned this issue Jan 17, 2025
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@jikunshang
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@vijaypal89 thanks for your input, fixed in this PR #12149 please take a try.

@vijaypal89
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Thanks @jikunshang this fixes vllm issue TypeError: argument 'text': 'list' object cannot be converted to 'PyString'

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[Bugfix] Mistral tokenizer encode accept list of str jikunshang/vllm
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@vijaypal89 @jikunshang