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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 cache_train(self):
 """ Loads the data for this classifier from a cache file :return: whether or not we were successful :rtype: bool """

        filename = self.get_cache_location()

        if not os.path.exists(filename):
            return False

        categories = pickle.load(open(filename, 'rb'))

        assert isinstance(categories, BayesCategories), \
            "Cache data is either corrupt or invalid"

        self.categories = categories

        # Updating our per-category overall probabilities
        self.calculate_category_probability()

        return True