cogdl.models.nn.pyg_sortpool
¶
Module Contents¶
Functions¶
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class
cogdl.models.nn.pyg_sortpool.
SortPool
(in_feats, hidden_dim, num_classes, num_layers, out_channel, kernel_size, k=30, dropout=0.5)[source]¶ Bases:
cogdl.models.BaseModel
Implimentation of sortpooling in paper “An End-to-End Deep Learning Architecture for Graph Classification” <https://www.cse.wustl.edu/~muhan/papers/AAAI_2018_DGCNN.pdf>__.
- in_featsint
Size of each input sample.
- out_featsint
Size of each output sample.
- hidden_dimint
Dimension of hidden layer embedding.
- num_classesint
Number of target classes.
- num_layersint
Number of graph neural network layers before pooling.
- kint, optional
Number of selected features to sort, default:
30
.- out_channelint
Number of the first convolution’s output channels.
- kernel_sizeint
Size of the first convolution’s kernel.
- dropoutfloat, optional
Size of dropout, default:
0.5
.