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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 compare_vectorized(self, comp_func, labels_left, labels_right, *args, **kwargs):
 """Compute the similarity between values with a callable. This method initialises the comparing of values with a custom function/callable. The function/callable should accept numpy.ndarray's. Example ------- Parameters comp_func : function A comparison function. This function can be a built-in function or a user defined comparison function. The function should accept numpy.ndarray's as first two arguments. labels_left : label, pandas.Series, pandas.DataFrame The labels, Series or DataFrame to compare. labels_right : label, pandas.Series, pandas.DataFrame The labels, Series or DataFrame to compare. *args : Additional arguments to pass to callable comp_func. **kwargs : Additional keyword arguments to pass to callable comp_func. (keyword 'label' is reserved.) label : (list of) label(s) The name of the feature and the name of the column. IMPORTANT: This argument is a keyword argument and can not be part of the arguments of comp_func. """

        label = kwargs.pop('label', None)

        if isinstance(labels_left, tuple):
            labels_left = list(labels_left)

        if isinstance(labels_right, tuple):
            labels_right = list(labels_right)

        feature = BaseCompareFeature(
            labels_left, labels_right, args, kwargs, label=label)
        feature._f_compare_vectorized = comp_func

        self.add(feature)