Installations

We will be using the OSCER supercomputer this semester. Having a configuration of python/tensorflow/keras/jupyter on your own machine is good, too. You want to be using Tensorflow 2.4.0 or better for this class.

Miniconda

Miniconda is a minimalist installation of Anaconda. Since we only need a subset of packages, this approach will use much less disk space.

Installation through Miniconda from Config File

If you are not already using Anaconda or Miniconda, download and install Miniconda
- It will prompt you as to whether you should init the environment. Answer yes
- I prefer not to automatically activate the base environment when you first create a shell:
```
conda config --set auto_activate_base false
```
- Then activate the default environment:
```
conda activate
```
- Download the anaconda environment description files:
  - environment_dlp_2023.txt (intended for machines with GPU)

Then do the following:

conda create --name tf --file environment_dlp_2023.txt

Once completed, when you start a new shell, you can activate your environment using:
```
conda activate tf
       
```

Installation through Miniconda by Hand

Download and install Miniconda
- It will prompt you as to whether you should init the environment. Answer yes
- I prefer not to automatically activate the base environment when you first create a shell:
```
conda config --set auto_activate_base false
```

Then do the following (the choice of "tf" is arbitrary):

conda update -n base -c defaults conda
conda create --name tf
conda activate tf
       
conda install mamba tensorflow -c conda-forge
       OR
conda install mamba tensorflow-gpu -c conda-forge
       
mamba install scikit-learn gym pypng matplotlib pandas bitarray jupyterlab pydot scikit-image keras-tuner xarray tensorflow-probability seaborn -c conda-forge
mamba install scikit-learn-intelex -c conda-forge
mamba install geopy opencv -c conda-forge

Once completed, when you start a new shell, you can activate your environment using:
```
conda activate tf       
```

Jupyter Lab

Jupyter Lab is an interactive development environment that you should only be using on your local machine (never on the supercomputer!). It is useful for quickly testing out ideas and code before you execute experiments.

If you followed the instructions above, then you already have Jupyter Lab installed. Otherwise ... Jupyter Lab installation

Useful software to support jupyter:

pandoc (need executable and python package)
xelatex (executable)

Supercomputer

In general, you do not need to install your own copy of python/tensorflow/keras. Instead, you can reference mine.

Execute:
```
. /home/fagg/tf_setup.sh
```
Alternatively, you can add the following line to the end of your .bashrc file:
```
. /home/fagg/tf_setup.sh
```
This will automatically set your conda paths up every time you login to the supercomputer.
Activate the environment:
```
conda activate tf
```

Of course, you will not be able to install additional packages into my space (if you want something, please ask).

andrewhfagg AT gmail.com

Last modified: Wed Mar 15 16:57:53 2023