在樓主寫這篇教程貼的時候,距離tensorflow2.0發佈已過去近6個月了。樓主在高三暑假時購入了jetson nano,但是由於學業比較繁忙,所以板子一直喫灰了。大一寒假正好時間比較多,所以開始繼續折騰jetson nano了。並將自己學習jetson nano時的經驗進行分享。這樣既方便自己後期溯源,又能方便對jetson nano感興趣的人快速入門,少走彎路。
開源地址:
gitee:www.gitee.com/xddcore/Jetson_Nano
github:www.github.com/xddcore/Jetson_Nano
PS:本篇教程基於目前(2020.1.20)我上傳在gitee的教程整理,如需最新教程和代碼,還請訪問gitee或github。(喜歡的朋友可以點個Star呀,瘋狂暗示)
教程正文開始(請大家原諒我三腳貓的英語水平QAQ)
tensorflow 2.0 pack
How to get tensorflow_gpu-2.0.0+nv19.11-cp36-cp36m-linux_aarch64.whl?
鏈接:https://pan.baidu.com/s/19YReceD2QxgcUwmxgZBqdA
提取碼:o2yh
How to ues?
pip3 install tensorflow_gpu-2.0.0+nv19.11-cp36-cp36m-linux_aarch64.whl --user
PS:
0.The python version is must be 3.6
1.The pip version is must be 19.3.1
2.The python setuptools version is must be >=41.0.0
3.The pyasn1-moduled version is must be >=0.2.1
4.The grpcio version is must be >=1.24.3
These have some information to help your achieve above software’s evironment:
if your don’t have pip,you need run:
sudo apt-get install python3-pip python3-dev
if your pip version is too low, you can run:
pip install --upgrade pip --user
and then 1:
sudo vim /usr/bin/pip3
modified file to:
#!/usr/bin/python3
# GENERATED BY DEBIAN
import sys
# Run the main entry point, similarly to how setuptools does it, but because
# we didn't install the actual entry point from setup.py, don't use the
# pkg_resources API.
from pip import __main__
if __name__ == '__main__':
sys.exit(__main__._main())
and then 2:
sudo vim /usr/local/bin/pip3
modified file to:
#!/usr/bin/python3
# -*- coding: utf-8 -*-
import re
import sys
from pip import __main__
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(__main__._main())
If you run:
pip3 -V
and the terminal print:
pip 19.3.1 from xxxxx #the xxxxx is your url
and the pip 19.3.1 install is success!
if your python setuptools version is too low,you can run:
pip3 install --upgrade setuptools --user
and then the setuptools will be upgrade!
if your pyasn1-modules version is too low,you can run:
pip3 install --upgrade pyasn1-modules --user
and then the pyasn1-modules will be upgrade!
if your grpcio version is too low,you can run:
pip3 install --upgrade grpcio --user
and then the grpcio will be upgrade!
In the end, When you finish above step,and then enter code in terminal:
python3
import tensorflow as tf
tf.__version__
The terminal will print:
'2.0.0'