TX2 搭建pytorch v0.1.10

一、环境: Ubuntu16.04、 cuda8.0

二、方法:1.mkdir -p ~/dl/pytorch

                    2.下载pytorch,注意下载的版本,此次搭建成功的是V 0.1.10。下载地址:https://github.com/pytorch/pytorch

                    3.cd ~/dl/pytorch,将下载的pytorch解压后的文件放在该文件夹下。(4和5都在该文夹下)

                    4.sudo vim pytorch_jetson_install.sh,建立脚本文件。文件内容如下,然后./pytorch_jetson_install.sh运行该文件(   或sh   pytorch_jetson_install.sh)

#!/bin/bash
#
# pyTorch install script for NVIDIA Jetson TX1/TX2,
# from a fresh flashing of JetPack 2.3.1 / JetPack 3.0 / JetPack 3.1
#
# for the full source, see jetson-reinforcement repo:
#   https://github.com/dusty-nv/jetson-reinforcement/blob/master/CMakePreBuild.sh
#
# note:  pyTorch documentation calls for use of Anaconda,
#        however Anaconda isn't available for aarch64.
#        Instead, we install directly from source using setup.py
sudo apt-get install python-pip

# upgrade pip
pip install -U pip
pip --version
# pip 9.0.1 from /home/ubuntu/.local/lib/python2.7/site-packages (python 2.7)

# clone pyTorch repo
cd pytorch
git init
git submodule update --init

# install prereqs
sudo pip install -U setuptools
sudo pip install -r requirements.txt

# Develop Mode:
python setup.py build_deps
sudo python setup.py develop

# Install Mode:  (substitute for Develop Mode commands)
#sudo python setup.py install

# Verify CUDA (from python interactive terminal)
# import torch
# print(torch.__version__)
# print(torch.cuda.is_available())
# a = torch.cuda.FloatTensor(2)
# print(a)
# b = torch.randn(2).cuda()
# print(b)
# c = a + b
# print(c)

5.测试,vim   test.py 内容如下

import torch
print(torch.cuda.is_available())
a = torch.cuda.FloatTensor(2)
print(a)
b = torch.randn(2).cuda()
print(b)
c = a + b
print(c)

然后运行,python  test.py

输出结果如下:

True


 0
 0
[torch.cuda.FloatTensor of size 2 (GPU 0)]


 0.6851
-0.3392
[torch.cuda.FloatTensor of size 2 (GPU 0)]


 0.6851
-0.3392
[torch.cuda.FloatTensor of size 2 (GPU 0)]

参考:

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转载自blog.csdn.net/qq_41980584/article/details/84035231