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An open framework for automatic modulation classification.

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Create the .condarc file if it does not exist.

touch ~/.condarc

Then copy the following mirrors to the .condarc:

channels:
  - http://mirrors.bfsu.edu.cn/anaconda/pkgs/main
  - http://mirrors.bfsu.edu.cn/anaconda/pkgs/free
  - http://mirrors.bfsu.edu.cn/anaconda/pkgs/r
  - http://mirrors.bfsu.edu.cn/anaconda/pkgs/pro
  - http://mirrors.bfsu.edu.cn/anaconda/pkgs/msys2
show_channel_urls: true
custom_channels:
  conda-forge: http://mirrors.bfsu.edu.cn/anaconda/cloud
  msys2: http://mirrors.bfsu.edu.cn/anaconda/cloud
  bioconda: http://mirrors.bfsu.edu.cn/anaconda/cloud
  menpo: http://mirrors.bfsu.edu.cn/anaconda/cloud
  pytorch: http://mirrors.bfsu.edu.cn/anaconda/cloud
  simpleitk: http://mirrors.bfsu.edu.cn/anaconda/cloud
  intel: http://mirrors.bfsu.edu.cn/anaconda/cloud

Then clean the cache

conda update --strict-channel-priority --all  

conda clean -i 

With tencent cloud, create the pip configuration file by mkdir ~/.pip; nano ~/.pip/pip.conf, and paste the following:

[global]
index-url = https://mirrors.cloud.tencent.com/pypi/simple/

[install]
trusted-host=mirrors.cloud.tencent.com

timeout = 120

Create the required env.

cd _requirement
conda create --name amc --file packages.txt
conda activate amc
conda install pip
pip install -r requirements.txt

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