def batch_generator()

in ncf.py [0:0]

• 17 lines of code
• 5 McCabe index (conditional complexity)

def batch_generator(x, y, batch_size, n_batch, shuffle, user_dim, item_dim):
    """ batch generator to supply data for training and testing """

    user_df, item_df = x

    counter = 0
    training_index = np.arange(user_df.shape[0])

    if shuffle:
        np.random.shuffle(training_index)

    while True:
        batch_index = training_index[batch_size*counter:batch_size*(counter+1)]
        user_batch = tf.one_hot(user_df[batch_index], depth=user_dim)
        item_batch = tf.one_hot(item_df[batch_index], depth=item_dim)
        y_batch = y[batch_index]
        counter += 1
        yield [user_batch, item_batch], y_batch

        if counter == n_batch:
            if shuffle:
                np.random.shuffle(training_index)
            counter = 0