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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_movielens_iter(filename, batch_size):
 """Not particularly fast code to parse the text file and load into NDArrays. return two data iters, one for train, the other for validation. """

    logging.info("Preparing data iterators for " + filename + " ... ")
    user = []
    item = []
    score = []
    with open(filename, 'r') as f:
        num_samples = 0
        for line in f:
            tks = line.strip().split('::')
            if len(tks) != 4:
                continue
            num_samples += 1
            user.append((tks[0]))
            item.append((tks[1]))
            score.append((tks[2]))
    # convert to ndarrays
    user = mx.nd.array(user, dtype='int32')
    item = mx.nd.array(item)
    score = mx.nd.array(score)
    # prepare data iters
    data_train = {'user': user, 'item': item}
    label_train = {'score': score}
    iter_train = mx.io.NDArrayIter(data=data_train,label=label_train,
                                   batch_size=batch_size, shuffle=True)
    return mx.io.PrefetchingIter(iter_train)