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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 _check_input_symbols(self, X):
 """Check if ``X`` is a sample from a Multinomial distribution. That is ``X`` should be an array of non-negative integers from range ``[min(X), max(X)]``, such that each integer from the range occurs in ``X`` at least once. For example ``[0, 0, 2, 1, 3, 1, 1]`` is a valid sample from a Multinomial distribution, while ``[0, 0, 3, 5, 10]`` is not. """

        symbols = np.concatenate(X)
        if (len(symbols) == 1                                # not enough data
            or not np.issubdtype(symbols.dtype, np.integer)  # not an integer
            or (symbols < 0).any()):                         # not positive
            return False
        u = np.unique(symbols)
        return u[0] == 0 and u[-1] == len(u) - 1