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Jetson?NX?配置?pytorch的問(wèn)題及解決方法

更新時(shí)間：2023年03月29日 14:32:48 作者：液壓姬

這篇文章主要介紹了Jetson?NX?配置?pytorch的相關(guān)知識(shí)，本文給大家介紹的非常詳細(xì)，對(duì)大家的學(xué)習(xí)或工作具有一定的參考借鑒價(jià)值，需要的朋友可以參考下

Jetson NX 配置pytorch

備注：參考博客最后安裝的pytorch無(wú)法使用cuda-----目前沒(méi)找到原因，不知如何解決。
但是官方的教程沒(méi)問(wèn)題！

環(huán)境情況：系統(tǒng)JetPack 5.0.2 --ubuntu20.04 配置流程安裝miniconda（流程省略）conda create -n pytorch python=3.8 安裝pytorch

sudo apt-get -y update;

sudo apt-get -y install autoconf bc build-essential g++-8 gcc-8 clang-8 lld-8 gettext-base gfortran-8 iputils-ping libbz2-dev libc++-dev libcgal-dev libffi-dev libfreetype6-dev libhdf5-dev libjpeg-dev liblzma-dev libncurses5-dev libncursesw5-dev libpng-dev libreadline-dev libssl-dev libsqlite3-dev libxml2-dev libxslt-dev locales moreutils openssl python-openssl rsync scons python3-pip libopenblas-dev;

sudo apt-get install python3-pip libopenblas-base libopenmpi-dev

conda activate pytorch

pip3 install Cython

添加環(huán)境變量

export PATH=/usr/local/cuda/bin:$PATH

export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

export CUDA_ROOT=/usr/local/cuda

export TORCH_INSTALL=https://developer.download.nvidia.cn/compute/redist/jp/v51/pytorch/torch-1.14.0a0+44dac51c.nv23.02-cp38-cp38-linux_aarch64.whl

python3 -m pip install --upgrade pip; python3 -m pip install aiohttp numpy=='1.19.4' scipy=='1.5.3'; python3 -m pip install --upgrade protobuf; python3 -m pip install --no-cache $TORCH_INSTALL

torchvision pip install torchvision

測(cè)試結(jié)果

>>> import torch
>>> print(torch.__version__)
>>> print('CUDA available: ' + str(torch.cuda.is_available()))
>>> print('cuDNN version: ' + str(torch.backends.cudnn.version()))
>>> a = torch.cuda.FloatTensor(2).zero_()
>>> print('Tensor a = ' + str(a))
>>> b = torch.randn(2).cuda()
>>> print('Tensor b = ' + str(b))
>>> c = a + b
>>> print('Tensor c = ' + str(c))
>>> import torchvision
>>> print(torchvision.__version__)

配合repvgg的部署 pip install opencv-contrib-pythonpip install matplotlibpip install torchvision 其他問(wèn)題

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