Installation#

There are various ways to use GiGL, depending on your preferred environment. These are the current environments supported by GiGL

The easiest way to set up gigl is to install it using pip. However, before installing the package, make sure you have the following prerequisites:

PyTorch Version: 2.1.2 (see PyTorch Installation Docs)
Torchvision Version: 0.16.2
Torchaudio Version: 2.1.2

To simplify this process, the steps to create a new conda enviornment and install gigl (and its dependencies) are shown below (seperated by platform/OS).

Installation Steps#

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:::{tab-item} ARM Mac

Create the conda environment (python 3.9)

conda create -y -c conda-force --name ANY_NAME python=3.9 pip-tools

Activate the newly created environment:

conda activate ANY_NAME

Install prerequisites

conda install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 -c pytorch -y

Install GiGL

pip install gigl[torch21-cpu, transform]

:::

:::{tab-item} Linux CPU

Create the conda environment (python 3.9)

conda create -y -c conda-force --name ANY_NAME python=3.9 pip-tools

Activate the newly created environment:

conda activate ANY_NAME

Install prerequisites

conda install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 cpuonly -c pytorch -y

Install GiGL

pip install gigl[torch21-cpu, transform]

:::

:::{tab-item} Linux CUDA 11.8

Create the conda environment (python 3.9)

conda create -y -c conda-forge --name ANY_NAME python=3.9 pip-tools

Activate the newly created environment:

conda activate ANY_NAME

Install prerequisites

conda install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=11.8 -c pytorch -c nvidia

Install GiGL

pip install gigl[torch21-cuda-118, transform]

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