GCN node classifier

gcn_node_classifier.py

from torch_geometric.nn import GCNConv
import torch.nn.functional as F

class GCN(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.conv1 = GCNConv(dataset.num_node_features, 16)
        self.conv2 = GCNConv(16, dataset.num_classes)

    def forward(self, data):
        x, edge_index = data.x, data.edge_index

        x = self.conv1(x, edge_index)
        x = F.relu(x)
        output = self.conv2(x, edge_index)

        return output
    
    
gcn = GCN().to(device)
optimizer_gcn = torch.optim.Adam(gcn.parameters(), lr=0.01, weight_decay=5e-4)
criterion = nn.CrossEntropyLoss()
gcn = train_node_classifier(gcn, graph, optimizer_gcn, criterion)

test_acc = eval_node_classifier(gcn, graph, graph.test_mask)
print(f'Test Acc: {test_acc:.3f}')