class_docstr: Abstract class for autogluon Learners. Learners encompass the learning problem end to end,
  including loading initial data, feature generation, model training, model prediction. Similar
  to Trainers, they implement `fit` and `predict` methods. The abstract method also includes
  concrete implementations of serialization/deserialization methods. Refer to individual
  documentations of concrete learner classes for further information.
code: def save_info(self, include_model_info=False):
      info = self.get_info(include_model_info=include_model_info)
  
      save_pkl.save(
          path=os.path.join(self.path, self.learner_info_name),
          object=info,
      )
      save_json.save(
          path=os.path.join(self.path, self.learner_info_json_name),
          obj=info,
      )
      return info
  
imports: import os
  import random
  import sys
  from typing import Optional, Type
  from autogluon.core.trainer import AbstractTrainer
  from autogluon.core.utils.loaders import load_pkl
  from autogluon.core.utils.savers import save_json, save_pkl
label_desc: Use image node_id 14 for calling the AbstractLearner obj's underlying member method code with example usage: obj.save_info(include_model_info) and returns: info