![]() Now, the installation work has been done and it should work well in most of the cases. In my case : conda create -p /home/pliu/pliup圓 python=3.6Ĭonda install -c nvidia cuda-toolkit=10.1.168 Note: if there are multiple users creating their own envs separately, please make sure the name of each env is unique. Note: the answers to all questions during installation are Yes except for the last question:ĭo you wish to proceed with the installation of Microsoft VSCode? Ī) cd ananconda3/bin export PATH =/location/ anaconda3 / bin : $PATH In my case: export PATH =/home/pengliu/ anaconda3 / bin : $PATHī) conda create -p /location/yourenvname python=x.x I am able to use VScode to edit my files and even run Jupyter notebook. During installation, I allowed anaconda environment to load along with ubuntu whenever I load ubuntu on wsl2. Note: replace “latest” with the version of anaconda, in this case: bash Anaconda3-5.2.0-Linux-x86_64.sh Since I am working with pandas library and python, I have also installed anaconda on ubuntu. ![]() This command line will start to download the anaconda installation package. We assume you’ve already installed CUDA.Ī) choose your system from the RED rectangle Here, I choose Ubuntu (Linux)ī) get the downloading link from the BLUE rectangle by right click In this tutorial, I would like to make a very quick and straightforward guideline that can lead most of us to start an enjoyable trip of deep learning. Recently, many times of environment installations push me to consider of writing a tutorial for saving time.
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