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capsule
dgmg
gat
gcn
jtnn
line_graph
rgcn
transformer
tree_lstm
README.md
pagerank.py

README.md

Model Examples using DGL (w/ Pytorch backend)

Each model is hosted in their own folders. Please read their README.md to see how to run them.

To understand step-by-step how these models are implemented in DGL. Check out our tutorials

Model summary

Here is a summary of the model accuracy and training speed. Our testbed is Amazon EC2 p3.2x instance (w/ V100 GPU).

Model Reported
Accuracy
DGL
Accuracy
Author's training speed (epoch time) DGL speed (epoch time) Improvement
GCN 81.5% 81.0% 0.0051s (TF) 0.0042s 1.17x
TreeLSTM 51.0% 51.72% 14.02s (DyNet) 3.18s 4.3x
R-GCN
(classification)
73.23% 73.53% 0.2853s (Theano) 0.0273s 10.4x
R-GCN
(link prediction)
0.158 0.151 2.204s (TF) 0.633s 3.5x
JTNN 96.44% 96.44% 1826s (Pytorch) 743s 2.5x
LGNN 94% 94% n/a 1.45s n/a
DGMG 84% 90% n/a 238s n/a