code: def _init_ensemble(self, features: list):
      self._set_max_features(len(features))
      self.data = [self._new_base_model() for _ in range(self.n_models)]
  
imports: from __future__ import annotations
  import abc
  import collections
  import copy
  import math
  import random
  import typing
  import numpy
  from river import base, metrics, stats
  from river.drift import ADWIN, NoDrift
  from river.tree.hoeffding_tree_classifier import HoeffdingTreeClassifier
  from river.tree.hoeffding_tree_regressor import HoeffdingTreeRegressor
  from river.tree.nodes.arf_htc_nodes import RandomLeafMajorityClass, RandomLeafNaiveBayes, RandomLeafNaiveBayesAdaptive
  from river.tree.nodes.arf_htr_nodes import RandomLeafAdaptive, RandomLeafMean, RandomLeafModel
  from river.tree.splitter import Splitter
  from river.utils.random import poisson
label_desc: Use image node_id 10 for calling the BaseForest obj's underlying member method code with example usage: obj._init_ensemble(features) without return types