textDataset.vectorizer.vocabulary_size, embeddings, freeze_embeddings=True) gcn_model = GCN(nFeat, nHid, nComm) criterion = nn.CrossEntropyLoss() optimizer = torch.optim.Adam(filter(lambda p: p.requires_grad, model.parameters()), lr=args.learning_rate, weight_decay=5e-4) gcn_optimizer = torch.optim.Adam(filter(lambda p: p.requires_grad, gcn_model.parameters()), lr=args.learning_rate, weight_decay=5e-4) if args.use_cuda: model.cuda() gcn_model.cuda() X_train = X_train.cuda() X_test = X_test.cuda() Y_train = Y_train.cuda() Y_test = Y_test.cuda() epoch_loss = [] epoch_accuracy = [] train_accuracy = [] epochs = [] correct = 0 try: for epoch in range(1, args.num_epochs + 1):