code: def configuration_fully_fitted(self):
      if self.estimator is None:
          return False
      elif not hasattr(self, "_fully_fit"):
          return False
      else:
          return self._fully_fit
  
file_path: auto-sklearn/autosklearn/pipeline/components/regression/mlp.py
imports: from typing import Optional
  import numpy
  from ConfigSpace.conditions import InCondition
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, Constant, UniformFloatHyperparameter, UniformIntegerHyperparameter, UnParametrizedHyperparameter
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnRegressionAlgorithm, IterativeComponent
  from autosklearn.pipeline.constants import DENSE, PREDICTIONS, SPARSE, UNSIGNED_DATA
  from autosklearn.util.common import check_for_bool
label_desc: Use image node_id 5 for calling the MLPRegressor obj's underlying member method code with example usage: obj.configuration_fully_fitted() and returns: False, False, self