DGL
0.7.x

Get Started

  • Install and Setup
  • A Blitz Introduction to DGL

Advanced Materials

  • User Guide
  • 用户指南
  • Stochastic Training of GNNs
  • Training on Multiple GPUs
  • Distributed training
  • Paper Study with DGL

API Reference

  • dgl
  • dgl.data
  • dgl.dataloading
  • dgl.DGLGraph
  • dgl.distributed
  • dgl.function
  • dgl.geometry
  • dgl.nn
    • NN Modules (PyTorch)
    • NN Modules (MXNet)
    • NN Modules (Tensorflow)
  • dgl.nn.functional
  • dgl.ops
  • dgl.optim
  • dgl.sampling
  • dgl.multiprocessing
  • User-defined Functions

Notes

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

Misc

  • Frequently Asked Questions (FAQ)
  • Environment Variables
  • Resources
DGL
  • »
  • dgl.nn
  • Edit on GitHub

dgl.nn¶

Package for pytorch-specific NN modules.

  • NN Modules (PyTorch)
    • Conv Layers
      • GraphConv
      • EdgeWeightNorm
      • RelGraphConv
      • TAGConv
      • GATConv
      • EdgeConv
      • SAGEConv
      • SGConv
      • APPNPConv
      • GINConv
      • GatedGraphConv
      • GMMConv
      • ChebConv
      • AGNNConv
      • NNConv
      • AtomicConv
      • CFConv
      • DotGatConv
      • TWIRLSConv
      • TWIRLSUnfoldingAndAttention
      • GCN2Conv
    • Dense Conv Layers
      • DenseGraphConv
      • DenseSAGEConv
      • DenseChebConv
    • Global Pooling Layers
      • SumPooling
      • AvgPooling
      • MaxPooling
      • SortPooling
      • WeightAndSum
      • GlobalAttentionPooling
      • Set2Set
      • SetTransformerEncoder
      • SetTransformerDecoder
    • Heterogeneous Graph Convolution Module
      • HeteroGraphConv
    • Utility Modules
      • Sequential
      • WeightBasis
      • KNNGraph
      • SegmentedKNNGraph
    • NodeEmbedding Module
      • NodeEmbedding
  • NN Modules (MXNet)
    • Conv Layers
      • GraphConv
      • RelGraphConv
      • TAGConv
      • GATConv
      • EdgeConv
      • SAGEConv
      • SGConv
      • APPNPConv
      • GINConv
      • GatedGraphConv
      • GMMConv
      • ChebConv
      • AGNNConv
      • NNConv
    • Dense Conv Layers
      • DenseGraphConv
      • DenseSAGEConv
      • DenseChebConv
    • Global Pooling Layers
      • SumPooling
      • AvgPooling
      • MaxPooling
      • SortPooling
      • GlobalAttentionPooling
      • Set2Set
    • Heterogeneous Graph Convolution Module
      • HeteroGraphConv
    • Utility Modules
      • Sequential
  • NN Modules (Tensorflow)
    • Conv Layers
      • GraphConv
      • RelGraphConv
      • GATConv
      • SAGEConv
      • ChebConv
      • SGConv
      • APPNPConv
      • GINConv
    • Global Pooling Layers
      • SumPooling
      • AvgPooling
      • MaxPooling
      • SortPooling
      • GlobalAttentionPooling
    • Heterogeneous Graph Convolution Module
      • HeteroGraphConv
Previous Next

© Copyright 2018, DGL Team. Revision de0eb209.

Built with Sphinx using a theme provided by Read the Docs.
Read the Docs v: 0.7.x
Versions
latest
0.7.x
0.6.x
0.5.x
0.4.x
0.3.x
0.2.x
0.1.x
Downloads
On Read the Docs
Project Home
Builds