背景:在服务器上搭建anaconda环境,已下载好以下文件:
- anaconda3.5.2.0-Linux-x86_64.sh
- tensorflow_gpu-1.14.0-cp37-cp37m-manylinux1_x86_64.whl
- Keras-2.2.4-py2.py3-none-any.whl
- opencv_contrib_python-4.1.0.25-cp37-cp37m-manylinux1_x86_64.whl
1. 安装anaconda
- 下载Anaconda最新.sh文件
wget https://mirrors.tuna.tsinghua.edu.cn./anaconda/archive/anaconda3.5.2.0-Linux-x86_64.sh
-
ls
命令查看
(因为服务器上已有文件,所以前两步已省略) -
bash Anaconda3.sh
安装,一路enter、yes - 重启账户即可看到当前用户目录下已有anaconda文件夹
2.安装tensorflow和Keras
- 新建虚拟环境:
conda create -n myenv python=3.7
- **环境:
source activate myenv
-
conda list
可查看当前已安装的包 -
pip install tensorflow_gpu-1.14.0-cp37-cp37m-manylinux1_x86_64.whl
-
pip install Keras-2.2.4-py2.py3-none-any.whl
-
pip install opencv_contrib_python-4.1.0.25-cp37-cp37m-manylinux1_x86_64.whl
3. 安装jupyter
- 退出**环境:
source deactivate myenv
conda install jupyter
4. mac连接服务器jupyter
- 打开terminal,输入
ssh -N -L localhost...
- 打开浏览器,输入,再输入登录服务器的当前用户的密码
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