code: def samples(self, gp, Y_metadata=None):
          
          orig_shape = gp.shape
          gp = gp.flatten()
          #orig_shape = gp.shape
          gp = gp.flatten()
          Ysim = np.array([np.random.normal(self.gp_link.transf(gpj), scale=np.sqrt(self.variance), size=1) for gpj in gp])
          return Ysim.reshape(orig_shape)
docs: Returns a set of samples of observations based on a given value of the latent variable.
  
          :param gp: latent variable