def METHOD_NAME(model, model_path, dataloader, source, data_name):
    model.load_state_dict(torch.load(model_path))
    model.to(DEVICE)
    model.eval()
    fea = torch.zeros(1, 501).to(DEVICE)
    with torch.no_grad():
        for inputs, labels in dataloader:
            inputs, labels = inputs.to(DEVICE), labels.to(DEVICE)
            x = model.get_feature(inputs)
            x = x.view(x.size(0), -1)
            labels = labels.view(labels.size(0), 1).float()
            x = torch.cat((x, labels), dim=1)
            fea = torch.cat((fea, x), dim=0)
    fea_numpy = fea.cpu().numpy()
    np.savetxt('{}_{}.csv'.format(source, data_name), fea_numpy[1:], fmt='%.6f', delimiter=',')
    print('{} - {} done!'.format(source, data_name))