class_docstr: TimeSeriesLearner encompasses a full time series learning problem for a
  training run, and keeps track of datasets, features, and the trainer object.
class_docstr_tok: ["TimeSeriesLearner","encompasses","a","full","time","series","learning","problem","for","a","training","run",",","and","keeps","track","of","datasets",",","features",",","and","the","trainer","object","."]
code: def get_info(
      self, include_model_info: bool = False, **kwargs
  ) -> Dict[str, Any]:
      learner_info = super().get_info(
          include_model_info=include_model_info
      )
      trainer = self.load_trainer()
      trainer_info = trainer.get_info(
          include_model_info=include_model_info
      )
      learner_info.update(
          {
              "time_fit_training": self._time_fit_training,
              "time_limit": self._time_limit,
          }
      )
  
      learner_info.update(trainer_info)
      # self.random_state not used during fitting, so we don't include it in the summary
      # TODO: Report random seed passed to predictor.fit?
      learner_info.pop("random_state", None)
      return learner_info
  
imports: import logging
  import reprlib
  import time
  from typing import Any, Dict, List, Optional, Type, Union
  import pandas
  from autogluon.core.learner import AbstractLearner
  from autogluon.timeseries.dataset.ts_dataframe import TimeSeriesDataFrame
  from autogluon.timeseries.metrics import TimeSeriesScorer, check_get_evaluation_metric
  from autogluon.timeseries.models.abstract import AbstractTimeSeriesModel
  from autogluon.timeseries.splitter import AbstractWindowSplitter
  from autogluon.timeseries.trainer import AbstractTimeSeriesTrainer, AutoTimeSeriesTrainer
  from autogluon.timeseries.utils.features import TimeSeriesFeatureGenerator
  from autogluon.timeseries.utils.forecast import get_forecast_horizon_index_ts_dataframe
label_desc: Use image node_id 10 for calling the TimeSeriesLearner obj's underlying member method code with example usage: obj.get_info(include_model_info) and returns: learner_info