code: def get_weights(self):
          
          if self.is_trained() is False:
              # print("Model not fitted yet. Use object.fit() to fit the model.")
              return None
  
          var_res = self._var_res
          weights = self._var_res_to_weights(var_res)
          # save to the side
          weights["final_bias_fit"] = weights["final_bias"]
          weights["feature_weights_fit"] = weights["feature_weights"]
  
          return weights
docs: Returns:
              dict: Model's trained weights.