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)
