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InternLM / lmdeploy

LMDeploy is a toolkit for compressing, deploying, and serving LLMs.
https://lmdeploy.readthedocs.io/en/latest/
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[Bug] Follow the Quick guide to run LLaVA, but a TypeError #2091

Open whwu95 opened 4 months ago

whwu95 commented 4 months ago

Checklist

Describe the bug

File "/fsx/wenhao/software/miniconda3/lib/python3.12/site-packages/lmdeploy/vl/model/llava.py", line 176, in forward image_features = self.encode_images(concat_images) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/fsx/wenhao/software/miniconda3/lib/python3.12/site-packages/lmdeploy/vl/model/llava.py", line 143, in encode_images image_features = self.mm_projector(image_features) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/fsx/wenhao/software/miniconda3/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl return self._call_impl(*args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/fsx/wenhao/software/miniconda3/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl return forward_call(*args, *kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/fsx/wenhao/software/miniconda3/lib/python3.12/site-packages/torch/nn/modules/container.py", line 217, in forward input = module(input) ^^^^^^^^^^^^^ File "/fsx/wenhao/software/miniconda3/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl return self._call_impl(args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/fsx/wenhao/software/miniconda3/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl return forward_call(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/fsx/wenhao/software/miniconda3/lib/python3.12/site-packages/torch/nn/modules/linear.py", line 116, in forward return F.linear(input, self.weight, self.bias) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: linear(): argument 'input' (position 1) must be Tensor, not tuple

Reproduction

from lmdeploy import pipeline from lmdeploy.vl import load_image

pipe = pipeline('liuhaotian/llava-v1.6-vicuna-7b')

image = load_image('https://raw.githubusercontent.com/open-mmlab/mmdeploy/main/tests/data/tiger.jpeg') response = pipe(('describe this image', image)) print(response)

Environment

sys.platform: linux
Python: 3.12.4 | packaged by Anaconda, Inc. | (main, Jun 18 2024, 15:12:24) [GCC 11.2.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-40GB
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 12.1, V12.1.105
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
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 8.9.5  (built against CUDA 12.2)
    - Built with 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: 4.40.0
gradio: 4.38.1
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  NV12    NV12    NV12    NV12    NV12    NV12    NV12    0-23,48-71  0       N/A
GPU1    NV12     X  NV12    NV12    NV12    NV12    NV12    NV12    0-23,48-71  0       N/A
GPU2    NV12    NV12     X  NV12    NV12    NV12    NV12    NV12    0-23,48-71  0       N/A
GPU3    NV12    NV12    NV12     X  NV12    NV12    NV12    NV12    0-23,48-71  0       N/A
GPU4    NV12    NV12    NV12    NV12     X  NV12    NV12    NV12    24-47,72-95 1       N/A
GPU5    NV12    NV12    NV12    NV12    NV12     X  NV12    NV12    24-47,72-95 1       N/A
GPU6    NV12    NV12    NV12    NV12    NV12    NV12     X  NV12    24-47,72-95 1       N/A
GPU7    NV12    NV12    NV12    NV12    NV12    NV12    NV12     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

lvhan028 commented 4 months ago

I didn't reproduce the issue. Here are my steps:

pip install lmdeploy
pip install git+https://github.com/haotian-liu/LLaVA.git --no-deps

test code:

from lmdeploy import pipeline
from lmdeploy.vl import load_image

pipe = pipeline('liuhaotian/llava-v1.6-vicuna-7b')

image = load_image('https://raw.githubusercontent.com/open-mmlab/mmdeploy/main/tests/data/tiger.jpeg')
response = pipe(('describe this image', image))
print(response)

Can you create a new environment and follow the above steps to reproduce it again?