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Installation

Supported Environments

These are the current environments supported by GiGL

Python Mac (Arm64) CPU Linux CPU Linux CUDA PyTorch PyG
3.9 Partial Support Supported 12.1 2.5 2.5

Available Versions

You can see the available wheels for GiGL here

Install Prerequisites - setting up your dev machine

Below we provide two ways to bootstrap an environment for using and/or developing GiGL

:color: primary

  1. Create dev instance
  We will need to create a GCP instance and setup needed pre-requisites to install and use GiGL.

  You can use our `create_dev_instance.py` script to automatically create an instance for you:
  ```bash
    python <(curl -s https://raw.githubusercontent.com/Snapchat/GiGL/refs/heads/main/scripts/create_dev_instance.py)
  ```
  Next, ssh into your instance. It might ask you to install gpu drivers, follow instructions and do so.

  2. Install some pre-reqs on your instance. The script below tries to automate installation of the following pre-reqs:
  `make, unzip, qemu-user-static, docker, docker-buildx, mamba/conda`
  ```bash
    bash -c "$(curl -s https://raw.githubusercontent.com/Snapchat/GiGL/refs/heads/main/scripts/scripts/startup_dev_instance.sh)"
  ```

  3. Once you are done, make sure to restart the instance. You may also need to navigate to the GCP compute instance UI, and under the `Observability` tab of your instance click the "Install OPS Agent" button under the GPU metrics to ensure the GPU metrics are also being reported.

  Next, Follow instructions to [install GiGL](#install-gigl)


:color: primary

  1. If on MAC, Install [Homebrew](https://brew.sh/).

  2. Install [Docker](https://docs.docker.com/desktop/) and the relevant `buildx` drivers (if using old versions of docker):

      Once installed, ensure you can run multiarch docker builds by running following command:

      Linux:
      ```bash
      docker buildx create --driver=docker-container --use
      sudo apt-get install qemu-user-static
      docker run --rm --privileged multiarch/qemu-user-static --reset -p yes
      ```

      Mac:
      ```bash
      docker buildx create --driver=docker-container --use
      brew install qemu
      docker run --rm --privileged multiarch/qemu-user-static --reset -p yes
      ```

  4. Ensure you have make installed.

      ```bash
      make --version
      ```

      **Install make on Linux:**
      ```
      apt-get update && apt-get upgrade -y && apt-get install -y cmake
      ```

      **Install make on MAC:**
      ```bash
      brew install make
      ```

      Subsequently, you should be able to use `gmake` in all places where we use `make` since brew formula has installed GNU "make" as "gmake".
      See: https://formulae.brew.sh/formula/make


  5. Follow the glcoud cli install [instructions](https://cloud.google.com/sdk/docs/install)

  6. Then, setup your gcloud environment:

    ```bash
    gcloud init # setup glcoud CLI
    gcloud auth application-default login # Auth gcloud cli
    gcloud auth configure-docker us-central1-docker.pkg.dev # Setup docker auth for GiGL images.
    ```

Install GiGL

Install Wheel

  1. Create a python virtual environment w/ python==3.11.*

  2. Install GiGL

Install GiGL + necessary tooling for PyG 2.7 + Torch 2.8 on Cuda12.8

pip install "gigl[pyg27-torch28-cu128, transform]==0.1.0" \
--extra-index-url=https://us-central1-python.pkg.dev/external-snap-ci-github-gigl/gigl/simple/ \
--extra-index-url=https://download.pytorch.org/whl/cu128 \
--extra-index-url=https://data.pyg.org/whl/torch-2.8.0+cu128.html

Currently, building/using wheels for GLT is error prone, thus we opt to install from source every time. Run post-install script to setup GLT dependency:

gigl-post-install

Install GiGL + necessary tooling for PyG 2.7 + Torch 2.8 on CPU

pip install "gigl[pyg27-torch28-cpu, transform]==0.1.0" \
--extra-index-url=https://us-central1-python.pkg.dev/external-snap-ci-github-gigl/gigl/simple/ \
--extra-index-url=https://download.pytorch.org/whl/cpu \
--extra-index-url=https://data.pyg.org/whl/torch-2.8.0+cpu.html

Currently, building/using wheels for GLT is error prone, thus we opt to install from source every time. Run post-install script to setup GLT dependency:

gigl-post-install

Install from source

git clone https://github.com/Snapchat/GiGL.git

If you are just using (not developing) GiGL, from the root directory:

make install_deps

If you instead want to contribute and/or extend GiGL. You can install the developer deps which includes some extra tooling:

make install_dev_deps