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  2. ubuntu安装python3.5+pycharm+anaconda+opencv+docker+nvidia-docker+tensorflow+pytorch+Cmake3.8

ubuntu安装python3.5+pycharm+anaconda+opencv+docker+nvidia-docker+tensorflow+pytorch+Cmake3.8

由 风格不统一 提交于 2019-12-10 11:30:53

一，切换python版本为3.5

装好ubuntu，python版本是2.7的

我自己安装并更改打开为python3.5

sudo apt-get install python3.5

设置优先级和默认环境：

sudo update-alternatives --install /usr/bin/python python /usr/bin/python2 100

sudo update-alternatives --install /usr/bin/python python /usr/bin/python3 150

切换版本：

update-alternatives --config python

可看见python已经为3.5了。

二，安装pycharm:

pycharm官网 https://www.jetbrains.com/pycharm/download/#section=linux

下载了这个，然后解压

启动pycharm,

下面激活：


添加下面一行到hosts文件，目的是屏蔽掉Pycharm对激活码的验证
0.0.0.0 account.jetbrains.com

打开PyCharm，选择Activate code（用激活码激活）

激活网址：http://idea.lanyus.com/

复制下载激活码，填入激活码框。

K6IXATEF43-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-KUaQi549fH96M/qU7jTvuMeq2GuedA+WppV3irI0JHlfDuhJlidK2m3yoRxitGNmimPFVUA8Dk38OzXnP29I39QDXH5VAF8VjOP0XrqdfrpaZUKpdhRaYz8r1NAwID75U4LqYCvFbazka1dCMJBFqJ2wum1+CSQhJ1O7CSchAJAbjcCRQjbU2sXOofAA2sPLi7nlJw2wrjOHzH9cOczUn11n24PE9BQ/oYGITHkzsu94i4Q90Z1jQysMtXLgM/HoLSHY2T9rKULLoh+tdMwBp9+m0VLF/R5gdkVDV/dlorrA9OEZIsSOaG+oWSen/AulKH6OXllZJoR+b/T6YYfGWg==-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

三，安装anaconda

下载python3.5对应的版本

https://repo.anaconda.com/archive/

然后：

~$ cd 下载
~/下载$ bash Anaconda2-4.2.0-Linux-x86_64.sh

这里需要一直按Enter，直到出现需要输入yes or no 。输入yes后，会显示Anaconda将要安装到哪个目录下，可以自行修改，这里我选择默认的路径，直接回车。最后会提示添加环境变量，输入yes后，安装完成。

pycharm中更改解释器路径。

ok,，结束。

卸载anaconda

首先直接删除整个anaconda文件夹，在vim ~/.bashrc

注释掉#  export PATH="/home/fzh/anaconda2/bin:$PATH"

最后在source  ~/.bashrc

重启终端

更换conda源

将以上配置文件写在~/.condarc中
vim ~/.condarc

channels:
  - https://mirrors.ustc.edu.cn/anaconda/pkgs/main/
  - https://mirrors.ustc.edu.cn/anaconda/cloud/conda-forge/
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
  - defaults
show_channel_urls: true

安装opencv

pip install opencv-contrib-python

pip install opencv-python

四，安装docker

docker/nvidia-docker 操作指南

https://www.dongliwu.com/archives/61/#directory0824639160743786413

若先前有安装docker需要先卸载（若没有安装过则无需执行），执行命令： 
sudo apt-get remove docker docker-engine docker.io 
Docker的安装有多个方式，这里以最常见的方式为例。首先依次执行以下命令，把docker仓库加进到apt里.

sudo apt-get update
sudo apt-get install apt-transport-https ca-certificates curl software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo apt-key fingerprint 0EBFCD88
sudo add-apt-repository  "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
正式安装docker： 
sudo apt-get update 
sudo apt-get install docker-ce 
apt-cache madison docker-ce 
sudo docker run hello-world 
最后一个命令是验证docker是否安装成功，它会下载并执行hello-world镜像。如果安装正确，应该可以正确执行。如果提示找不到,多重复几次即可.

五,安装nvidia-docker

# 清理以前的。If you have nvidia-docker 1.0 installed: we need to remove it and all existing GPU containers
sudo docker volume ls -q -f driver=nvidia-docker | xargs -r -I{} -n1 docker ps -q -a -f volume={} | xargs -r docker rm -f
sudo apt-get purge -y nvidia-docker
sudo apt autoremove
 
# 执行命令。Add the package repositories
# command 1
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | \
  sudo apt-key add -
 
# command 2
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
 
# command 3
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
  sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update
 
# 正式安装。Install nvidia-docker2 and reload the Docker daemon configuration
sudo apt-get install -y nvidia-docker2
sudo pkill -SIGHUP dockerd
 
# 测试一下。 Test nvidia-smi with the latest official CUDA image
sudo docker run --runtime=nvidia --rm nvidia/cuda:9.0-base  nvidia-smi

 

我利用有驱动的官方镜像安装其他环境，首先把docker跑起来

sudo nvidia-docker run -it  nvidia/cuda:9.0-base

apt-get update

apt-get upgrade

接下来，完善此镜像。安装完整的cuda-toolkit：
官方的镜像不完整，这一步很关键

apt install cuda-toolkit-9-0

apt-get install python3

apt-get install python3-pip

然后按照这个链接去装cuda和cudnn即可.

https://blog.csdn.net/fanzonghao/article/details/89707519

想要更新原来的镜像,比如上述都安转好了,用commit命令,adaf25712ec8是原有镜像的id,chaos_gpu是新镜像的名字,用docker images即可查看新的镜像

commit后面是ps出来的容器ID，后面跟自己想要保存的名字，我这里是chaos_gpu

sudo nvidia-docker commit adaf25712ec8 chaos_gpu

保持镜像到本地：

https://www.runoob.com/docker/docker-save-command.html

将镜像 runoob/ubuntu:v3 生成 my_ubuntu_v3.tar 文档

docker save -o my_ubuntu_v3.tar runoob/ubuntu:v3

载入本地镜像：

docker load -i tf_torch_gpu.tar

进入镜像 docker run --runtime nvidia -it ufoym/deepo:tensorflow-py36 bash

六.下载使用TensorFlow镜像
根据需要的版本下载tensorflow镜像并开启tensorflow容器： 

https://github.com/alibaba/x-deeplearning/wiki/%E7%BC%96%E8%AF%91%E5%AE%89%E8%A3%85?from=singlemessage

七.安装tensorflow

pip3 install tensorflow-gpu==1.12.0

import tensorflow as tf
a=tf.constant(1)
with tf.Session() as sess:
    print(sess.run(a))

八.安装pytorch

https://pytorch.org/get-started/locally/

安装torch官网根据cuda版本来安装

conda install pytorch torchvision cudatoolkit=9.0 -c pytorch

其中，-c pytorch参数指定了conda获取pytorch的channel,在此指定为conda自带的pytorch仓库。
因此，只需要将-c pytorch语句去掉，就可以使用清华镜像源快速安装pytorch了。

若要安装指定版本的pytorch

pip install torch==0.4.0

import torch
print(torch.version.cuda)
print(torch.cuda.is_available())
print(torch.__version__)

如果出现fasle,去检查cuda是否装好

最终挂载本地与docker同步命令

nvidia-docker run -it -v ~/AI/:/AI -w /AI/  --name=fzh_tf_torch_py3 -p 2111:22 -p 2112:6006 -p 2113:8888 tf_pytorch_gpu:1.12.0_1.1.0 bash

九,安装Cmake3.8

官网下载cmake https://cmake.org/files/v3.8/

vim ~/.bashrc  添加环境变量

source ~/.bashrc 激活

cmake --version

 

参考:

https://blog.csdn.net/WannaSeaU/article/details/88427010

 

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