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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 marginal_loglike(self, x):
 """Marginal log-likelihood. Returns ``L_marg(x) = \int L(x,y|z') L(y) dy`` This will used the cached '~fermipy.castro.Interpolator' object if possible, and construct it if needed. """

        if self._marg_interp is None:
            # This calculates values and caches the spline
            return self._marginal_loglike(x)

        x = np.array(x, ndmin=1)
        return self._marg_interp(x)