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Overview

A deep learning library focused on graph representation learning for real-world chemical tasks.

  • ✅ State-of-the-art GNN architectures.
  • 🐍 Extensible API: build your own GNN model and train it with ease.
  • ⚗️ Rich featurization: powerful and flexible built-in molecular featurization.
  • 🧠 Pretrained models: for fast and easy inference or transfer learning.
  • ⮔ Read-to-use training loop based on Pytorch Lightning.
  • 🔌 Have a new dataset? Graphium provides a simple plug-and-play interface. Change the path, the name of the columns to predict, the atomic featurization, and you’re ready to play!

Installation

For CPU or GPU

Use mamba:

# Install Graphium
mamba install -c conda-forge graphium

or pip:

pip install graphium

For IPU

# Install Graphcore's SDK and Graphium dependencies in a new environment called `.graphium_ipu`
./install_ipu.sh .graphium_ipu

The above step needs to be done once. After that, enable the SDK and the environment as follows:

source enable_ipu.sh .graphium_ipu

Finally, you will need to install graphium with pip 

pip install graphium