code: def get_metadata_routing(self):
      router = (
          MetadataRouter(owner=self.__class__.__name__)
          .add_self_request(self)
          .add(estimator=self.estimator, method_mapping="one-to-one")
      )
      return router
  
imports: import warnings
  from pprint import pprint
  import numpy
  from sklearn import set_config
  from sklearn.base import BaseEstimator, ClassifierMixin, MetaEstimatorMixin, RegressorMixin, TransformerMixin, clone
  from sklearn.linear_model import LinearRegression
  from sklearn.utils import metadata_routing
  from sklearn.utils.metadata_routing import MetadataRouter, MethodMapping, get_routing_for_object, process_routing
  from sklearn.utils.validation import check_is_fitted
label_desc: Use image node_id 2 for calling the RouterConsumerClassifier obj's underlying member method code with example usage: obj.get_metadata_routing() and returns: router