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):
