code: def get_parameters(self, params, graph=None):
          
          g = graph if graph is not None else self.tf_graph
  
          with g.as_default():
              with tf.Session() as self.tf_session:
                  self.tf_saver.restore(self.tf_session, self.model_path)
                  out = {}
                  for par in params:
                      if type(params[par]) == list:
                          for i, p in enumerate(params[par]):
                              out[par + '-' + str(i+1)] = p.eval()
                      else:
                          out[par] = params[par].eval()
                  return out
docs: Get the parameters of the model.
  
          :param params: dictionary of keys (str names) and values (tensors).
          :return: evaluated tensors in params