DGL
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Get Started

  • Install DGL
  • DGL at a Glance
  • DGL Basics
  • PageRank with DGL Message Passing
  • Batched Graph Classification with DGL

Features

  • Builtin message passing functions

Model Tutorials

  • Model overview
  • Graph Neural Network and its variant
  • Dealing with many small graphs
  • Generative models
  • Old (new) wines in new bottle
  • Training on giant graphs

API Reference

  • API Reference
    • DGLGraph – Graph with node/edge features
    • Feature Initializer
    • BatchedDGLGraph – Enable batched graph operations
    • Builtin functions
    • Graph Traversal
    • Message Propagation
    • User-defined function related data structures
    • Graph samplers
    • Dataset
    • Transform – Graph Transformation
    • dgl.nn
      • dgl.nn.pytorch
      • dgl.nn.mxnet
    • DGLSubGraph – Class for subgraph data structure
    • Graph Store – Graph for multi-processing and distributed training
    • NodeFlow – Graph sampled from a large graph

Developer Notes

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

Misc

  • FAQ
  • Environment Variables
  • Resources
DGL
  • Docs »
  • API Reference »
  • dgl.nn
  • Edit on GitHub

dgl.nn¶

Package for neural network common components.

  • dgl.nn.pytorch
    • dgl.nn.pytorch.conv
    • dgl.nn.pytorch.glob
    • dgl.nn.pytorch.softmax
  • dgl.nn.mxnet
    • dgl.nn.mxnet.conv
    • dgl.nn.mxnet.glob
    • dgl.nn.mxnet.softmax
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