code: def get_regressors() -> List[Candidate]:
      """Get a list of available regressors."""
      _regressors = []
      try:
          from sklearn.neural_network.multilayer_perceptron import (
              MLPRegressor,
          )
      except ImportError:
          pass
      else:
          _regressors.append(MLPRegressor)
      for e in _regressors:
          yield Candidate(name=e.__name__, clazz=e, create=e)
  
file_path: sklearn-porter/tests/commons/__init__.py
imports: from collections import namedtuple
  from os import environ
  from pathlib import Path
  from typing import List
  from sklearn.ensemble.forest import ExtraTreesClassifier, RandomForestClassifier
  from sklearn.ensemble.weight_boosting import AdaBoostClassifier
  from sklearn.naive_bayes import BernoulliNB, GaussianNB
  from sklearn.neighbors.classification import KNeighborsClassifier
  from sklearn.svm import SVC, LinearSVC, NuSVC
  from sklearn.tree.tree import DecisionTreeClassifier
  import sklearn
  from sklearn.datasets import load_digits, load_iris
label_desc: Use image node_id 2 for calling a global function with example usage: get_regressors() without return types