georgia-tech-db / eva / #850

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        """

        It will return a count of search element for each tuple.

        The idea is to flatten the input array along the first dimension and

        count the search element in this flattened array.

        For example,

        a tuple of shape (3,4,5) will be flattened into three (4,5) elements.

        And the search key is expected to be of shape (4,5),

        else we throw an error.

        frames: DataFrame

            col1        col2

        0   ndarray1    search_key

        1   ndarray2    search_key

        out: DataFrame

            count

        0   int

        1   int

        """

        # sanity check

            raise ValueError("input contains more than one column")

            lambda x: self.count_in_row(x[0], search_element), axis=1

        )

        # change the row and search element to numpy array

        # checks if dimension diff is one between

        # row_val and search_element

            raise ValueError("inconsistent dimensions for row value and search element")

        # reshape along the first dimension and then

        # check how many time search element exists