nets

Equinox (JAX) neural nets.

Quickstart

Clone the repo:

git clone [email protected]:eringrant/nets.git
cd nets/

To install a Conda environment with the requisite packages on CPU:

conda env create --file environment-cpu.yml

To test the code a quick debug run:

python -m nets.experiments.in_context_learning.launcher_local

Installation

Optionally, define a few environment variables by adding the following to a shell configuration file such as ~/.bashrc, ~/.bash_profile, ~/.bash_login, or ~/.profile:

export SCRATCH_HOME="..."

Then, follow one of two methods below to install nets.

Method #1: via Conda

Use Conda to develop nets code directly.

Option #1.1: CPU-only

To install via Mamba (recommended) or Conda, do:

conda env create --file environment-cpu.yml

Option #1.2: On GPU on a local machine

To install via Mamba (recommended) or Conda with GPU support, do:

conda env create --file environment-gpu.yml

Option #1.3: On GPU on a SLURM cluster

If working on the head node of a SLURM cluster, you will need to create a GPU-compatible environment on a compute node with an available GPU via:

srun --partition=gpu --gres=gpu:1 conda env create -f environment-gpu.yml

Note that you may have to adapt the partition name to the available partitions on your cluster; run sinfo -s to display details about partitions.

Method #2: via Pip

Use Pip in order to install this code as a package in another project.

Option #2.1: Command-line

python -m pip install git+https://github.com/eringrant/nets

Option #2.2: In a requirements file

nets @ git+https://github.com/eringrant/nets

Option #2.3: Locally & as an editable package

git clone [email protected]:eringrant/nets.git
cd nets/
python -m pip install -e .

Devtools

Pre-commit

.pre-commit-config.yaml has been configured to run several autoformatters. Run the following to install, update, and cache all pre-commit tools:

pre-commit install && pre-commit run