InternLM / lmdeploy

LMDeploy is a toolkit for compressing, deploying, and serving LLMs.
https://lmdeploy.readthedocs.io/en/latest/
Apache License 2.0
4.11k stars 373 forks source link

[Bug] InternVL2-Llama3-76B-AWQ使用--tp 4正常,但是单卡--tp 1返回的content为空 #2118

Open day9011 opened 1 month ago

day9011 commented 1 month ago

Checklist

Describe the bug

InternVL2-Llama3-76B-AWQ使用--tp 4正常,但是单卡--tp 1返回的content为空 --tp 1: res_json: {'id': '2', 'object': 'chat.completion', 'created': 1721788658, 'model': 'internvl2-test', 'choices': [{'index': 0, 'message': {'role': 'assistant', 'content': '', 'tool_calls': None}, 'logprobs': None, 'finish_reason': 'stop'}], 'usage': {'prompt_tokens': 3497, 'total_tokens': -288276476, 'completion_tokens': -288279973}} --tp 4: res_json: {'id': '213', 'object': 'chat.completion', 'created': 1721735823, 'model': 'internvl2-test', 'choices': [{'index': 0, 'message': {'role': 'assistant', 'content': 'json\n{\n "water": true,\n "message": "The image shows a significant amount of water covering the road surface, indicating a flooding issue."\n}\n', 'tool_calls': None}, 'logprobs': None, 'finish_reason': 'stop'}], 'usage': {'prompt_tokens': 2019, 'total_tokens': 2054, 'completion_tokens': 35}}

Reproduction

lmdeploy serve api_server /storage210_new/models/huggingface/internvl/InternVL2-Llama3-76B-AWQ/ --tp 1 --cache-max-entry-cou nt 0.01 --model-name internvl2-test

Environment

sys.platform: linux
Python: 3.10.14 (main, May  6 2024, 19:42:50) [GCC 11.2.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0,1,2,3,4,5,6,7: NVIDIA A800-SXM4-80GB
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 12.3, V12.3.103
GCC: gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
PyTorch: 2.2.2+cu121
PyTorch compiling details: PyTorch built with:
  - GCC 9.3
  - C++ Version: 201703
  - Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v3.3.2 (Git Hash 2dc95a2ad0841e29db8b22fbccaf3e5da7992b01)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - LAPACK is enabled (usually provided by MKL)
  - NNPACK is enabled
  - CPU capability usage: AVX512
  - CUDA Runtime 12.1
  - NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90
  - CuDNN 8.9.2
  - Magma 2.6.1
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=12.1, CUDNN_VERSION=8.9.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=2.2.2, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF,

TorchVision: 0.17.2+cu121
LMDeploy: 0.5.1+
transformers: 4.43.1
gradio: Not Found
fastapi: 0.111.1
pydantic: 2.8.2
triton: 2.2.0
NVIDIA Topology:
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV8     NV8     NV8     NV8     NV8     NV8     NV8     0-23,48-71      0               N/A
GPU1    NV8      X      NV8     NV8     NV8     NV8     NV8     NV8     0-23,48-71      0               N/A
GPU2    NV8     NV8      X      NV8     NV8     NV8     NV8     NV8     0-23,48-71      0               N/A
GPU3    NV8     NV8     NV8      X      NV8     NV8     NV8     NV8     0-23,48-71      0               N/A
GPU4    NV8     NV8     NV8     NV8      X      NV8     NV8     NV8     24-47,72-95     1               N/A
GPU5    NV8     NV8     NV8     NV8     NV8      X      NV8     NV8     24-47,72-95     1               N/A
GPU6    NV8     NV8     NV8     NV8     NV8     NV8      X      NV8     24-47,72-95     1               N/A
GPU7    NV8     NV8     NV8     NV8     NV8     NV8     NV8      X      24-47,72-95     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

Error traceback

No response

day9011 commented 1 month ago

image 使用tp1的时候报错

day9011 commented 1 month ago

--tp 2以上都没有问题

lvhan028 commented 1 month ago

日志中显示 invalid infer request for id 2, code=6, code=6 表示 input_prompt_token + max_new_tokens 超过了 session_len 了

day9011 commented 1 month ago

日志中显示 invalid infer request for id 2, code=6, code=6 表示 input_prompt_token + max_new_tokens 超过了 session_len 了

但是我使用--tp 2,完全一模一样的输入,就没有问题

day9011 commented 1 month ago

日志中显示 invalid infer request for id 2, code=6, code=6 表示 input_prompt_token + max_new_tokens 超过了 session_len 了

image

day9011 commented 1 month ago

这是--tp 1下的输出

lvhan028 commented 1 month ago

因为 tp=2,2卡,内存 kv cache 用。 使用 log-level INFO,仔细看下引擎测的日志

day9011 commented 1 month ago

--tp 1下的: image image image

--tp 2下的: image image image image