def train_pred(x_train, y_train, x_test, seed): print 'Building the CNN ...' rng = np.random.RandomState(seed) model = CNN(rng, .1) model.load_params('./param') print 'Training with early stop .. ' x_train, y_train, x_valid, y_valid = split_train_set(x_train, y_train) model.train(x_train, y_train, x_valid, y_valid) model.save_params('./param') pred = model.predict(x_test) write_data(pred)