1. Pycharm professional (requires an activation code) is installed on the machine and students can register with the education email to receive a free one-year activation code
  1. Import your own code package
  1. Click on the Tools – Start the SSH… Connecting to the server

  1. Click tools-deployment-configuration-connection /Mappings to select the local and server mapping folder

Auto upload Automatically uploads code

  1. Click File-settings-Project Interpreter to select the compilation environment

Then click Add-SSH Interpreter to connect to the virtual environment on the server (how to do that on the server next)

  1. Install Anonconda3 in your personal folder (/home/ XXX /)

Download the anaconda installation script (this tutorial tsinghua source) wget HTTP: / / https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2020.07-Linux-x86_64.sh

Install anaconda bash anaconda3-2020.07-linux-x86_64. sh. Press Y or press Enter

Refresh the current user environment (active environment) source ~/.bashrc

View the contents of environment variables to be modified. View the contents of environment variables configured in the installation script vim ~/.bashrc

if [ -f "/usr/local/anaconda3/etc/profile.d/conda.sh" ]; then
    . "/usr/local/anaconda3/etc/profile.d/conda.sh"
else
    export PATH="/usr/local/anaconda3/bin:$PATH"
fi
Copy the code

Configure the Anaconda environment for common users

Add the preceding content to the end of the text vim /etc/profile

This command is required to activate the environment each time you log in. The environment is automatically activated each time you log in. Switch to the default login user source /etc/profile

Anaconda Added or deleted virtual environments

Create a virtual environment conda create -n XXX python=3.6.5

Run the following command to delete the virtual environment: conda remove -n XXX –all

Anaconda Switches virtual environments

View the conda env list of all environments

Conda activate XXX is activated

Exit the conda deactivate XXX virtual environment

The original link: blog.csdn.net/caoyugangsg…

  1. Add the required package (tensorflow-GPU-1.15.0, Pillow 6.0) in file-settings-project Interpreter. 0, etc.)

  1. Install CUDA10.0 on your server because you are running on an NVIDIa-GPU. Each tensorFlow release may have a different GCC and CUDA release, so be sure to check the version number

Corresponding relations between

Download CUDA10.0, server ubantu18.04 is already configured with version 10.1

Wget HTTP: / / https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda_10.0.130_410.48_linux

Add the executable permission to sudo chmod +x cudA_10.0.130/410.48_linux

Modify configuration files and other operations, see the following blog

Blog.csdn.net/u012388993/…

Runtime code error ** CAN’t find CUDA 10.0**

Conda install CudatoolKit =10.0 in the server virtual environment

Run the code again, and you’re done

Check the GUP status of nvidia-SMI