Ascend
1 系统
NAME="Ubuntu" VERSION="20.04.6 LTS (Focal Fossa)" 昇腾910B2 驱动 23.0.6.2 CANN 7.5.X Miner U 2.1.9
2 踩坑记录
坑1： 图形库相关的问题，总之就是动态库导致TLS的内存分配失败（OpenCV库在ARM64架构上的兼容性问题） ⭐这个错误 ImportError: /lib/aarch64-linux-gnu/libGLdispatch.so.0: cannot allocate memory in static TLS block 是由于OpenCV库在ARM64架构上的兼容性问题导致的。从错误堆栈可以看到，问题出现在导入cv2模块时，这发生在MinerU的VLM后端初始化过程中。 解决方法： 1 安装减少内存问题的opencv版本
pip install --upgrade albumentations albucore simsimd# Uninstall current opencv
pip uninstall opencv-python opencv-contrib-python
# Install headless version (no GUI dependencies)
pip install opencv-python-headless
python -c "import cv2; print(cv2.__version__)"2 apt-get install一些包
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ focal main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ focal-updates main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ focal-backports main restricted universe multiverse
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ focal-security main restricted universe multiversesudo apt-get update -o Dir::Etc::sourcelist="sources.list.tuna" -o Dir::Etc::sourceparts="-" -o APT::Get::List-Cleanup="0"
sudo apt-get install libgl1-mesa-glx -o Dir::Etc::sourcelist="sources.list.tuna" -o Dir::Etc::sourceparts="-" -o APT::Get::List-Cleanup="0"
sudo apt-get install libglib2.0-0 libsm6 libxext6 libxrender-dev libgomp1 -o Dir::Etc::sourcelist="sources.list.tuna" -o Dir::Etc::sourceparts="-" -o APT::Get::List-Cleanup="0"
sudo apt-get install libgl1-mesa-dev libgles2-mesa-dev -o Dir::Etc::sourcelist="sources.list.tuna" -o Dir::Etc::sourceparts="-" -o APT::Get::List-Cleanup="0"
sudo apt-get install libgomp1 -o Dir::Etc::sourcelist="sources.list.tuna" -o Dir::Etc::sourceparts="-" -o APT::Get::List-Cleanup="0"
export OPENCV_IO_ENABLE_OPENEXR=0 export QT_QPA_PLATFORM=offscreen
3 强制覆盖conda环境自带的动态库（conda的和系统的冲突）
查找：find /usr/lib /lib /root/.local/conda -name "libgomp.so*" 2>/dev/null
export LD_PRELOAD="/usr/lib/aarch64-linux-gnu/libstdc++.so.6:/usr/lib/aarch64-linux-gnu/libgomp.so.1"
export LD_PRELOAD=/lib/aarch64-linux-gnu/libGLdispatch.so.0:$LD_PRELOAD
mv $CONDA_PREFIX/lib/libstdc++.so.6 $CONDA_PREFIX/lib/libstdc++.so.6.bak
mv $CONDA_PREFIX/lib/libgomp.so.1 $CONDA_PREFIX/lib/libgomp.so.1.bak
mv $CONDA_PREFIX/lib/libGLdispatch.so.0 $CONDA_PREFIX/lib/libGLdispatch.so.0.bak # 如果有的话
simsimd包相关：
mv /root/.local/conda/envs/pdfparser/lib/python3.10/site-packages/simsimd./libgomp-947d5fa1.so.1.0.0 /root/.local/conda/envs/pdfparser/lib/python3.10/site-packages/simsimd./libgomp-947d5fa1.so.1.0.0.bak
# 找到 scikit-learn 内部的 libgomp 路径
SKLEARN_LIBGOMP="/root/.local/conda/envs/pdfparser/lib/python3.10/site-packages/scikit_learn.libs/libgomp-947d5fa1.so.1.0.0"
# 预加载这个特定的 libgomp 版本
export LD_PRELOAD="$SKLEARN_LIBGOMP:$LD_PRELOAD"