code: def test_balancing_get_weights_treed_multilabel(self):
      Y = np.array(
          [[0, 0, 0]] * 100
          + [[1, 0, 0]] * 100
          + [[0, 1, 0]] * 100
          + [[1, 1, 0]] * 100
          + [[0, 0, 1]] * 100
          + [[1, 0, 1]] * 10
      )
      balancing = Balancing(strategy="weighting")
      init_params, fit_params = balancing.get_weights(
          Y, "adaboost", None, None, None
      )
      print(fit_params["classifier:sample_weight"])
      self.assertAlmostEqual(
          np.mean(fit_params["classifier:sample_weight"]),
          1,
      )
      np.testing.assert_allclose(
          fit_params["classifier:sample_weight"],
          np.array([0.85] * 500 + [8.5] * 10),
      )
  
imports: import copy
  import numpy
  import sklearn.datasets
  import sklearn.metrics
  from autosklearn.pipeline.classification import SimpleClassificationPipeline
  from autosklearn.pipeline.components.classification.adaboost import AdaboostClassifier
  from autosklearn.pipeline.components.classification.decision_tree import DecisionTree
  from autosklearn.pipeline.components.classification.extra_trees import ExtraTreesClassifier
  from autosklearn.pipeline.components.classification.gradient_boosting import GradientBoostingClassifier
  from autosklearn.pipeline.components.classification.liblinear_svc import LibLinear_SVC
  from autosklearn.pipeline.components.classification.libsvm_svc import LibSVM_SVC
  from autosklearn.pipeline.components.classification.passive_aggressive import PassiveAggressive
  from autosklearn.pipeline.components.classification.random_forest import RandomForest
  from autosklearn.pipeline.components.classification.sgd import SGD
  from autosklearn.pipeline.components.data_preprocessing.balancing.balancing import Balancing
  from autosklearn.pipeline.components.feature_preprocessing.extra_trees_preproc_for_classification import ExtraTreesPreprocessorClassification
  from autosklearn.pipeline.components.feature_preprocessing.liblinear_svc_preprocessor import LibLinear_Preprocessor
  import unittest
label_desc: Use image node_id 2 for calling the BalancingComponentTest obj's underlying member method code with example usage: obj.test_balancing_get_weights_treed_multilabel() without return types