DGL
0.5.x

Get Started

  • Install DGL
  • Working with different backends
  • DGL at a Glance

User Guide

  • Chapter 1: Graph
  • Chapter 2: Message Passing
  • Chapter 3: Building GNN Modules
  • Chapter 4: Graph Data Pipeline
  • Chapter 5: Training Graph Neural Networks
  • Chapter 6: Stochastic Training on Large Graphs
  • Chapter 7: Distributed Training

API Reference

  • dgl
  • dgl.data
  • dgl.dataloading
  • dgl.DGLGraph
  • dgl.distributed
  • dgl.function
  • dgl.nn
  • dgl.ops
  • dgl.sampling
  • User-defined Functions

Model Tutorials

  • Graph neural networks and its variants
  • Batching many small graphs
  • Generative models
  • Revisit classic models from a graph perspective

Developer Notes

  • Contribute to DGL
  • DGL Foreign Function Interface (FFI)

Misc

  • FAQ
  • Environment Variables
  • Resources
DGL
  • »
  • API Reference
  • Edit on GitHub

API ReferenceΒΆ

  • dgl
    • Graph Create Ops
    • Subgraph Extraction Ops
    • Graph Transform Ops
    • Batching and Reading Out Ops
    • Adjacency Related Utilities
    • Traversals
    • Utilities
  • dgl.data
    • Base Dataset Class
    • Node Prediction Datasets
    • Edge Prediction Datasets
    • Graph Prediction Datasets
    • Utilities
  • dgl.dataloading
    • DataLoaders
    • Neighbor Sampler
    • Negative Samplers for Link Prediction
  • dgl.DGLGraph
    • Querying metagraph structure
    • Querying graph structure
    • Querying and manipulating sparse format
    • Querying and manipulating node/edge ID type
    • Using Node/edge features
    • Transforming graph
    • Adjacency and incidence matrix
    • Computing with DGLGraph
    • Querying batch summary
    • Mutating topology
    • Device Control
    • Misc
  • dgl.distributed
    • Initialization
    • Distributed Graph
    • Distributed Tensor
    • Distributed Embedding
    • Distributed workload split
    • Distributed Sampling
    • Partition
  • dgl.function
    • DGL Built-in Function
    • Message functions
    • Reduce functions
  • dgl.nn
    • NN Modules (PyTorch)
    • NN Modules (MXNet)
    • NN Modules (Tensorflow)
  • dgl.ops
    • GSpMM functions
    • GSDDMM functions
    • Edge Softmax module
    • Relation with Message Passing APIs
  • dgl.sampling
    • Random walk
    • Neighbor sampling
  • User-defined Functions
    • Edge-wise User-defined Function
    • Node-wise User-defined Function
    • Degree Bucketing for Message Passing with User Defined Functions

© Copyright 2018, DGL Team Revision 0133f764.

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