04ad358395c7bd074ffb9af235ccb76d2c0dc4cc,examples/pna.py,,,#,62

Before Change

    return train_acc, val_acc, test_acc


for epoch in range(1, 301):
    train_loss, val_loss = train()
    print("Epoch: {:03d}, Loss: {:.8f}, Val Loss {:.8f}".format(epoch, train_loss, val_loss))

train_acc, val_acc, test_acc = test()
print("Accuracy: train: {:.4f} val: {:.4f} test: {:.4f}".format(train_acc, val_acc, test_acc))

After Change

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = Net().to(device)
optimizer = torch.optim.Adam(model.parameters(), lr=0.001)
scheduler = ReduceLROnPlateau(optimizer, mode="min", factor=0.5, patience=5,
                              min_lr=0.00001)


def train(epoch):
    model.train()

Instances