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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 cosine_similarity(evaluated_model, reference_model):
 """ Computes cosine similarity of two text documents. Each document has to be represented as TF model of non-empty document. :returns float: 0 <= cos <= 1, where 0 means independence and 1 means exactly the same. """

    if not (isinstance(evaluated_model, TfModel) and isinstance(reference_model, TfModel)):
        raise ValueError(
            "Arguments has to be instances of 'sumy.models.TfDocumentModel'")

    terms = frozenset(evaluated_model.terms) | frozenset(reference_model.terms)

    numerator = 0.0
    for term in terms:
        numerator += evaluated_model.term_frequency(term) * reference_model.term_frequency(term)

    denominator = evaluated_model.magnitude * reference_model.magnitude
    if denominator == 0.0:
        raise ValueError("Document model can't be empty. Given %r & %r" % (
            evaluated_model, reference_model))

    return numerator / denominator