class_docstr: A meta-model that trains the base model multiple times using different train/validation splits.
  
  Follows the logic of autogluon.core.models.ensembles.BaggedEnsembleModel.
  
  Parameters
  ----------
  model_base : Union[AbstractTimeSeriesModel, Type[AbstractTimeSeriesModel]]
      The base model to repeatedly train. If a AbstractTimeSeriesModel class, then also provide model_base_kwargs
      which will be used to initialize the model via model_base(**model_base_kwargs).
  model_base_kwargs : Optional[Dict[str, any]], default = None
      kwargs used to initialize model_base if model_base is a class.
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code: def _more_tags(self) -> dict:
      return self.most_recent_model._get_tags()
  
imports: import copy
  import inspect
  import logging
  import math
  import os
  import time
  from typing import Dict, Optional, Type, Union
  import numpy
  import autogluon.core
  from autogluon.common.utils.log_utils import set_logger_verbosity
  from autogluon.timeseries.dataset.ts_dataframe import TimeSeriesDataFrame
  from autogluon.timeseries.models.abstract import AbstractTimeSeriesModel
  from autogluon.timeseries.models.local.abstract_local_model import AbstractLocalModel
  from autogluon.timeseries.splitter import AbstractWindowSplitter, ExpandingWindowSplitter
label_desc: Use image node_id 19 for calling the MultiWindowBacktestingModel obj's underlying member method code with example usage: obj._more_tags() and returns: self