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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 predict(self, Xnew):
 """Prediction on the new data Parameters Xnew : array_like, shape = (n_samples, n_features) The test data. Returns ------- mean : array_like, shape = (n_samples, output.dim) Posterior mean at the location of Xnew var : array_like, shape = (n_samples, 1) Posterior variance at the location of Xnew """

        Xnew_warped = self.transform_data(Xnew, test_data=True)
        mean, var = super(InputWarpedGP, self).predict(Xnew_warped, kern=self.kernel, full_cov=False)
        return mean, var