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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 posterior_samples(self, X, size=10, full_cov=False, Y_metadata=None, likelihood=None, **predict_kwargs):
 """ Samples the posterior GP at the points X, equivalent to posterior_samples_f due to the absence of a likelihood. """

        return self.posterior_samples_f(X, size, full_cov=full_cov, **predict_kwargs)