class_docstr: This is the base estimator for gluoncv.auto.Estimators.
  
  Parameters
  ----------
  config : dict
      Config in nested dict.
  logger : logging.Logger
      Optional logger for this estimator, can be `None` when default setting is used.
  reporter : callable
      The reporter for metric checkpointing.
  name : str
      Optional name for the estimator.
  
  Attributes
  ----------
  _logger : logging.Logger
      The customized/default logger for this estimator.
  _logdir : str
      The temporary dir for logs.
  _cfg : autocfg.dataclass
      The configurations.
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code: def _fit(self, train_data, val_data, time_limit=math.inf):
      raise NotImplementedError
  
imports: import os
  import math
  import pickle
  import io
  import logging
  from datetime import datetime
  import numpy
  import pandas
  from ...utils import random
  from ...utils.filesystem import temporary_filename
  from .utils import _suggest_load_context
label_desc: Use image node_id 9 for calling the BaseEstimator obj's underlying member method code with example usage: obj._fit(train_data, val_data, time_limit) without return types