PyGCL Documentation

PyGCL is an open-source Graph Contrastive Learning (GCL) library for PyTorch, which features modularized GCL components from published papers, standardized evaluation, and experiment management.

It implements four main components of graph contrastive learning algorithms:

  • Graph augmentation: transforms input graphs into congruent graph views.

  • Contrasting architectures and modes: generate positive and negative pairs according to node and graph embeddings.

  • Contrastive objectives: computes the likelihood score for positive and negative pairs.

  • Negative mining strategies: improves the negative sample set by considering the relative similarity (the hardness) of negative sample.

It also implements utilities for training models, evaluating model performance, and managing experiments.

Contents

Package Reference

Indices and Tables