code: def from_dict(input_dict, data=None):
          
          import GPy
          m = GPy.core.model.Model.from_dict(input_dict, data)
          from copy import deepcopy
          sparse_gp = deepcopy(m)
          return SparseGPClassification(sparse_gp.X, sparse_gp.Y, sparse_gp.Z, sparse_gp.kern, sparse_gp.likelihood,  sparse_gp.inference_method, sparse_gp.mean_function, name='sparse_gp_classification')
docs: Instantiate an SparseGPClassification object using the information
          in input_dict (built by the to_dict method).
  
          :param data: It is used to provide X and Y for the case when the model
             was saved using save_data=False in to_dict method.
          :type data: tuple(:class:`np.ndarray`, :class:`np.ndarray`)