ocr开启cuda加速后，无法解析pdf

[huangyao1021]

Description of the bug | 错误描述

[11/07 16:23:16 d2.checkpoint.detection_checkpoint]: [DetectionCheckpointer] Loading from /root/.cache/modelscope/hub/opendatalab/PDF-Extract-Kit-1___0/models/Layout/LayoutLMv3/model_final.pth ...
[11/07 16:23:16 fvcore.common.checkpoint]: [Checkpointer] Loading from /root/.cache/modelscope/hub/opendatalab/PDF-Extract-Kit-1___0/models/Layout/LayoutLMv3/model_final.pth ...
[HAMI-core Msg(53365:140341461254656:memory.c:511)]: orig free=40618885120 total=42505273344 limit=42505076736 usage=1883242496
2024-11-07 16:23:22.830 | INFO | magic_pdf.model.pdf_extract_kit:init:302 - DocAnalysis init done!
2024-11-07 16:23:22.830 | INFO | magic_pdf.model.doc_analyze_by_custom_model:custom_model_init:131 - model init cost: 23.24226951599121

---

C++ Traceback (most recent call last):

0 at::_ops::conv2d::call(at::Tensor const&, at::Tensor const&, std::optionalat::Tensor const&, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, c10::SymInt)
1 at::native::conv2d_symint(at::Tensor const&, at::Tensor const&, std::optionalat::Tensor const&, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, c10::SymInt)
2 at::_ops::convolution::call(at::Tensor const&, at::Tensor const&, std::optionalat::Tensor const&, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, bool, c10::ArrayRefc10::SymInt, c10::SymInt)
3 at::_ops::convolution::redispatch(c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optionalat::Tensor const&, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, bool, c10::ArrayRefc10::SymInt, c10::SymInt)
4 at::native::convolution(at::Tensor const&, at::Tensor const&, std::optionalat::Tensor const&, c10::ArrayRef, c10::ArrayRef, c10::ArrayRef, bool, c10::ArrayRef, long)
5 at::_ops::_convolution::call(at::Tensor const&, at::Tensor const&, std::optionalat::Tensor const&, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, bool, c10::ArrayRefc10::SymInt, c10::SymInt, bool, bool, bool, bool)
6 at::native::_convolution(at::Tensor const&, at::Tensor const&, std::optionalat::Tensor const&, c10::ArrayRef, c10::ArrayRef, c10::ArrayRef, bool, c10::ArrayRef, long, bool, bool, bool, bool)
7 at::_ops::cudnn_convolution::call(at::Tensor const&, at::Tensor const&, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, c10::ArrayRefc10::SymInt, c10::SymInt, bool, bool, bool)
8 at::native::cudnn_convolution(at::Tensor const&, at::Tensor const&, c10::ArrayRef, c10::ArrayRef, c10::ArrayRef, long, bool, bool, bool)
9 cuLaunchKernel

---

Error Message Summary:

FatalError: Segmentation fault is detected by the operating system.
[TimeInfo: *** Aborted at 1730967804 (unix time) try "date -d @1730967804" if you are using GNU date ***]
[SignalInfo: *** SIGSEGV (@0x20000002ef4) received by PID 53365 (TID 0x7fa3caf20200) from PID 12020 ***]

段错误 (核心已转储)

How to reproduce the bug | 如何复现

absl-py 2.1.0
accelerate 1.1.1
aiohappyeyeballs 2.4.3
aiohttp 3.10.10
aiosignal 1.3.1
albucore 0.0.20
albumentations 1.4.21
annotated-types 0.7.0
antlr4-python3-runtime 4.9.3
anyio 4.6.2.post1
astor 0.8.1
async-timeout 4.0.3
attrdict 2.0.1
attrs 24.2.0
babel 2.16.0
bce-python-sdk 0.9.23
beautifulsoup4 4.12.3
black 24.10.0
blinker 1.8.2
boto3 1.35.55
botocore 1.35.55
braceexpand 0.1.7
Brotli 1.1.0
cachetools 5.5.0
certifi 2024.8.30
cffi 1.17.1
charset-normalizer 3.4.0
click 8.1.7
cloudpickle 3.1.0
colorlog 6.9.0
contourpy 1.3.0
cryptography 43.0.3
cssselect 1.2.0
cssutils 2.11.1
cycler 0.12.1
Cython 3.0.11
datasets 3.1.0
decorator 5.1.1
detectron2 0.6
dill 0.3.8
doclayout_yolo 0.0.2
einops 0.8.0
et_xmlfile 2.0.0
eva-decord 0.6.1
eval_type_backport 0.2.0
evaluate 0.4.3
exceptiongroup 1.2.2
fairscale 0.4.13
fast-langdetect 0.2.0
fasttext-wheel 0.9.2
filelock 3.16.1
fire 0.7.0
Flask 3.0.3
flask-babel 4.0.0
fonttools 4.54.1
frozenlist 1.5.0
fsspec 2024.9.0
ftfy 6.3.1
future 1.0.0
fvcore 0.1.5.post20221221
grpcio 1.67.1
h11 0.14.0
httpcore 1.0.6
httpx 0.27.2
huggingface-hub 0.26.2
hydra-core 1.3.2
idna 3.10
imageio 2.36.0
imgaug 0.4.0
iopath 0.1.9
itsdangerous 2.2.0
Jinja2 3.1.4
jmespath 1.0.1
joblib 1.4.2
kiwisolver 1.4.7
langdetect 1.0.9
lazy_loader 0.4
lmdb 1.5.1
loguru 0.7.2
lxml 5.3.0
magic-pdf 0.9.2
Markdown 3.7
MarkupSafe 3.0.2
matplotlib 3.9.2
modelscope 1.19.2
more-itertools 10.5.0
mpmath 1.3.0
multidict 6.1.0
multiprocess 0.70.16
mypy-extensions 1.0.0
networkx 3.4.2
numpy 1.26.4
nvidia-cublas-cu11 11.11.3.6
nvidia-cublas-cu12 12.1.3.1
nvidia-cuda-cupti-cu11 11.8.87
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu11 11.8.89
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu11 11.8.89
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu11 8.7.0.84
nvidia-cudnn-cu12 8.9.2.26
nvidia-cufft-cu11 10.9.0.58
nvidia-cufft-cu12 11.0.2.54
nvidia-curand-cu11 10.3.0.86
nvidia-curand-cu12 10.3.2.106
nvidia-cusolver-cu11 11.4.1.48
nvidia-cusolver-cu12 11.4.5.107
nvidia-cusparse-cu11 11.7.5.86
nvidia-cusparse-cu12 12.1.0.106
nvidia-nccl-cu11 2.19.3
nvidia-nccl-cu12 2.20.5
nvidia-nvjitlink-cu12 12.6.77
nvidia-nvtx-cu11 11.8.86
nvidia-nvtx-cu12 12.1.105
omegaconf 2.3.0
opencv-contrib-python 4.6.0.66
opencv-python 4.6.0.66
opencv-python-headless 4.10.0.84
openpyxl 3.1.5
opt-einsum 3.3.0
packaging 24.1
paddleocr 2.7.3
paddlepaddle 3.0.0b1
paddlepaddle-gpu 3.0.0b1
pandas 2.2.3
pathspec 0.12.1
pdf2docx 0.5.8
pdfminer.six 20231228
pillow 11.0.0
pip 24.2
platformdirs 4.3.6
portalocker 2.10.1
premailer 3.10.0
propcache 0.2.0
protobuf 5.28.3
psutil 6.1.0
py-cpuinfo 9.0.0
pyarrow 18.0.0
pybind11 2.13.6
pyclipper 1.3.0.post6
pycocotools 2.0.8
pycparser 2.22
pycryptodome 3.21.0
pydantic 2.7.4
pydantic_core 2.18.4
PyMuPDF 1.24.13
pyparsing 3.2.0
python-dateutil 2.9.0.post0
python-docx 1.1.2
pytz 2024.2
PyYAML 6.0.2
RapidFuzz 3.10.1
rarfile 4.2
regex 2024.11.6
requests 2.32.3
robust-downloader 0.0.2
s3transfer 0.10.3
safetensors 0.4.5
scikit-image 0.24.0
scikit-learn 1.5.2
scipy 1.14.1
seaborn 0.13.2
setuptools 75.1.0
shapely 2.0.6
simsimd 6.0.1
six 1.16.0
sniffio 1.3.1
soupsieve 2.6
stringzilla 3.10.8
struct-eqtable 0.3.2
sympy 1.13.3
tabulate 0.9.0
tensorboard 2.18.0
tensorboard-data-server 0.7.2
termcolor 2.5.0
thop 0.1.1.post2209072238
threadpoolctl 3.5.0
tifffile 2024.9.20
timm 0.9.16
tokenizers 0.19.1
tomli 2.0.2
torch 2.3.1
torchtext 0.18.0
torchvision 0.18.1
tqdm 4.67.0
transformers 4.42.4
triton 2.3.1
typing_extensions 4.12.2
tzdata 2024.2
ultralytics 8.3.28
ultralytics-thop 2.0.10
unimernet 0.2.1
urllib3 2.2.3
visualdl 2.5.3
Wand 0.6.13
wcwidth 0.2.13
webdataset 0.2.100
Werkzeug 3.1.2
wheel 0.44.0
xxhash 3.5.0
yacs 0.1.8
yarl 1.17.1

没开启cuda加速前，也就是没有执行这个命令前：python -m pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/ 一切正常
安装之后，没有任何包的冲突,安装之后重新执行命令就出现了解析失败的问题

Operating system | 操作系统

Linux

Python version | Python 版本

3.10

Software version | 软件版本 (magic-pdf --version)

0.9.x

Device mode | 设备模式

cuda

[myhloli]

有可能是cu118的paddle不兼容，您是H系列的显卡吗？

[huangyao1021]

有可能是cu118的paddle不兼容，您是H系列的显卡吗？

我的卡是A100的，有影响吗

[myhloli]

有可能是cu118的paddle不兼容，您是H系列的显卡吗？

我的卡是A100的，有影响吗

A100应该是没问题的

[lrybbbccc]

会不会是同时装了cuda11和12驱动的问题？看到你的pip list里面有

[userjiangxin]

I also encountered the same problem. The graphics card is RTX4090. Is the problem solved?