GraphSAGE
- class dhg.models.GraphSAGE(*args, **kwargs)[source]
Bases:
torch.nn.Module
The GraphSAGE model proposed in Inductive Representation Learning on Large Graphs paper (NIPS 2017).
- Parameters
in_channels (
int
) – \(C_{in}\) is the number of input channels.hid_channels (
int
) – \(C_{hid}\) is the number of hidden channels.num_classes (
int
) – The Number of class of the classification task.aggr (
str
) – The neighbor aggregation method. Currently, only mean aggregation is supported. Defaults to “mean”.use_bn (
bool
) – If set toTrue
, use batch normalization. Defaults toFalse
.drop_rate (
float
, optional) – The dropout probability. Defaults to 0.5.