code: def fit(self, X, y, sample_weight=None, **fit_params):
      params = process_routing(
          self, "fit", sample_weight=sample_weight, **fit_params
      )
      check_metadata(self, sample_weight=sample_weight)
      self.estimator_ = clone(self.estimator).fit(
          X, y, **params.estimator.fit
      )
  
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 WeightedMetaRegressor obj's underlying member method code with example usage: obj.fit(X, y, sample_weight) without return types