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.
docstr: Update the path where model, learner, and trainer objects will be saved.
  Also see `create_contexts`.
docstr_tok: ["Update","the","path","where","model",",","learner",",","and","trainer","objects","will","be","saved",".","Also","see","`","create_contexts","`","."]
code: def set_contexts(self, path_context: str):
      """Update the path where model, learner, and trainer objects will be saved.
      Also see `create_contexts`."""
      (
          self.path,
          self.model_context,
          self.save_path,
      ) = self.create_contexts(path_context)
  
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 3 for calling the AbstractLearner obj's underlying member method code with example usage: obj.set_contexts(path_context) without return types