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import torch
import torch.nn.functional as F
from torch_geometric.nn import FastRGCNConv
class RGCN(torch.nn.Module):
def __init__(self, in_channels, out_channels, num_relations):
super().__init__()
self.conv1 = FastRGCNConv(in_channels, 16, num_relations, num_bases=30)
self.conv2 = FastRGCNConv(16, out_channels, num_relations,
num_bases=30)
def forward(self, data):
edge_index, edge_type = data.edge_index, data.edge_type
x = F.relu(self.conv1(None, edge_index, edge_type))
x = self.conv2(x, edge_index, edge_type)
return F.log_softmax(x, dim=1)
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