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SETUP.md

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Getting started (on MOL)

We use (bio)conda throughout the course. Install from Terminal as described here. The default shell may be set to tcsh (not bash); therefore may need to switch to bash manually. Copy the following commands and run them in a terminal window.

bash
wget https://repo.anaconda.com/archive/Anaconda3-2023.09-0-Linux-x86_64.sh
bash Anaconda3-2023.09-0-Linux-x86_64.sh

For some commands below, do not copy the preceeding $ or >>> signs. They simply indicate commands compared to the output. Check the CUDA Toolkit version installed (11.7):

$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Jun__8_16:49:14_PDT_2022
Cuda compilation tools, release 11.7, V11.7.99
Build cuda_11.7.r11.7/compiler.31442593_0

Install the latest versions of PyTorch and associated packages still compatible with the CUDA version. The example below was obtained from the list of previous versions on the CUDA web site, and searching for 11.7. Run this command:

conda install pytorch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pytorch-cuda=11.7 -c pytorch -c nvidia

Continue by installing Pytorch Lightning and TensorBoard (lab 1-3) with this command:

conda install lightning tensorboard -c conda-forge

And the Transformers library form Hugging Face (lab 4):

conda install biopython transformers datasets evaluate -c conda-forge

After installing conda, close and reopen the terminal window, to make the installation available.

Quick check that the GPU is available from python:

$ python
Python 3.11.5 (main, Sep 11 2023, 13:54:46) [GCC 11.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch.cuda
>>> torch.cuda.is_available()
True
>>> exit()

Install git & download the course repository (see a blog post and a paper on using git):

conda install git
git clone https://github.com/evocellnet/bc_deep_learning_in_biology/

Go to the repository, and launch jupyter lab:

cd ~/bc_deep_learning/
jupyter lab

At the end of the course, please clean up anaconda, and remove the course repository/other files from the machine you've been using.