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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 _reduce_nbest_translations(nbest_translations_list: List[Translation]) -> Translation: """ Combines Translation objects that are nbest translations of the same sentence. :param nbest_translations_list: A list of Translation objects, all of them translations of the same source sentence. :return: A single Translation object where nbest lists are collapsed. """

    best_translation = nbest_translations_list[0]

    sequences = [translation.target_ids for translation in nbest_translations_list]
    attention_matrices = [translation.attention_matrix for translation in nbest_translations_list]
    scores = [translation.score for translation in nbest_translations_list]

    nbest_translations = NBestTranslations(sequences, attention_matrices, scores)

    return Translation(best_translation.target_ids,
                       best_translation.attention_matrix,
                       best_translation.score,
                       best_translation.beam_histories,
                       nbest_translations,
                       best_translation.estimated_reference_length)