Welcome to CogDL’s Documentation!¶
CogDL is a graph representation learning toolkit that allows researchers and developers to easily train and compare baseline or custom models for node classification, link prediction and other tasks on graphs. It provides implementations of many popular models, including: non-GNN Baselines like Deepwalk, LINE, NetMF, GNN Baselines like GCN, GAT, GraphSAGE.
CogDL provides these features:
Task-Oriented: CogDL focuses on tasks on graphs and provides corresponding models, datasets, and leaderboards.
Easy-Running: CogDL supports running multiple experiments simultaneously on multiple models and datasets under a specific task using multiple GPUs.
Multiple Tasks: CogDL supports node classification and link prediction tasks on homogeneous/heterogeneous networks, as well as graph classification.
Extensibility: You can easily add new datasets, models and tasks and conduct experiments for them!
- Node classification
- Link prediction
- Graph classification
- Graph pre-training
- Graph clustering
- Graph similarity search
- Base Task
- Node Classification
- Unsupervised Node Classification
- Node Classification (with sampling)
- Heterogeneous Node Classification
- Multiplex Node Classification
- Link Prediction
- Multiplex Link Prediction
- Graph Classification
- Unsupervised Graph Classification
- Attributed Graph Clustering
- Similarity Search
- Task Module