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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 has_duplicate_max(x):
 """ Checks if the maximum value of x is observed more than once :param x: the time series to calculate the feature of :type x: numpy.ndarray :return: the value of this feature :return type: bool """

    if not isinstance(x, (np.ndarray, pd.Series)):
        x = np.asarray(x)
    return np.sum(x == np.max(x)) >= 2