code: def convert_sklearn_random_forest_regressor(
      operator, device, extra_config
  ):
      """
      Converter for `sklearn.ensemble.RandomForestRegressor` and `sklearn.ensemble.ExtraTreesRegressor`
  
      Args:
          operator: An operator wrapping the RandomForestRegressor and ExtraTreesRegressor model
          device: String defining the type of device the converted operator should be run on
          extra_config: Extra configuration used to select the best conversion strategy
  
      Returns:
          A PyTorch model
      """
      assert operator is not None, "Cannot convert None operator"
  
      # Get tree information out of the operator.
      tree_infos = operator.raw_operator.estimators_
      n_features = operator.raw_operator.n_features_in_
  
      # For Sklearn Trees we need to know how many trees are there for normalization.
      extra_config[constants.NUM_TREES] = len(tree_infos)
  
      def get_parameters_for_tree_trav(
          lefts, rights, features, thresholds, values, extra_config={}
      ):
          return get_parameters_for_tree_trav_sklearn(
              lefts,
              rights,
              features,
              thresholds,
              values,
              None,
              extra_config,
          )
  
      return convert_decision_ensemble_tree_common(
          operator,
          tree_infos,
          get_parameters_for_sklearn_common,
          get_parameters_for_tree_trav,
          n_features,
          extra_config=extra_config,
      )
  
file_path: hummingbird/hummingbird/ml/operator_converters/sklearn/decision_tree.py
imports: import copy
  from onnxconverter_common.registration import register_converter
  from ..None import constants
  from .._tree_commons import get_parameters_for_sklearn_common, get_parameters_for_tree_trav_sklearn
  from .._tree_commons import convert_decision_ensemble_tree_common
label_desc: Use image node_id 2 for calling a global function with example usage: convert_sklearn_random_forest_regressor(operator, device, extra_config) and returns: convert_decision_ensemble_tree_common, get_parameters_for_tree_trav_sklearn