DGL
2.0.0
Get Started
Install and Setup
A Blitz Introduction to DGL
Advanced Materials
🆕 Stochastic Training of GNNs with GraphBolt
User Guide
用户指南【包含过时信息】
사용자 가이드[시대에 뒤쳐진]
Tutorials: dgl.sparse
Training on CPUs
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.graphbolt
dgl.nn (PyTorch)
Conv Layers
CuGraph Conv Layers
Dense Conv Layers
Global Pooling Layers
Score Modules for Link Prediction and Knowledge Graph Completion
Heterogeneous Learning Modules
Utility Modules
Sequential
WeightBasis
KNNGraph
SegmentedKNNGraph
RadiusGraph
JumpingKnowledge
NodeEmbedding
GNNExplainer
HeteroGNNExplainer
SubgraphX
HeteroSubgraphX
PGExplainer
HeteroPGExplainer
LabelPropagation
DegreeEncoder
BiasedMultiheadAttention
BiasedMultiheadAttention
EGTLayer
GraphormerLayer
PathEncoder
SpatialEncoder
SpatialEncoder3d
Network Embedding Modules
Utility Modules for Graph Transformer
dgl.nn (TensorFlow)
dgl.nn (MXNet)
dgl.nn.functional
dgl.ops
dgl.optim
dgl.sampling
dgl.sparse
dgl.multiprocessing
dgl.transforms
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 (PyTorch)
BiasedMultiheadAttention
View page source
BiasedMultiheadAttention
class
dgl.nn.pytorch.graph_transformer.
BiasedMultiheadAttention
(
*
args
:
Any
,
**
kwargs
:
Any
)
Bases:
Read the Docs
v: latest
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