code: def _assert_predict_proba_dict_identical_to_predict_proba(
      predictor: TabularPredictor, data
  ):
      """Assert that predict_proba_multi is identical to looping calls to predict_proba"""
      for as_pandas in [True, False]:
          for inverse_transform in [True, False]:
              for as_multiclass in [True, False]:
                  predict_proba_dict = predictor.predict_proba_multi(
                      data=data,
                      as_pandas=as_pandas,
                      as_multiclass=as_multiclass,
                      inverse_transform=inverse_transform,
                  )
                  assert set(predictor.model_names()) == set(
                      predict_proba_dict.keys()
                  )
                  for m in predictor.model_names():
                      if not inverse_transform:
                          model_pred_proba = (
                              predictor._learner.predict_proba(
                                  data,
                                  model=m,
                                  as_pandas=as_pandas,
                                  as_multiclass=as_multiclass,
                                  inverse_transform=inverse_transform,
                              )
                          )
                      else:
                          model_pred_proba = predictor.predict_proba(
                              data,
                              model=m,
                              as_pandas=as_pandas,
                              as_multiclass=as_multiclass,
                          )
                      if as_pandas:
                          assert model_pred_proba.equals(
                              predict_proba_dict[m]
                          )
                      else:
                          assert np.array_equal(
                              model_pred_proba, predict_proba_dict[m]
                          )
  
imports: import os
  import shutil
  import sys
  import tempfile
  import warnings
  from random import seed
  import numpy
  import pandas
  import pytest
  from networkx.exception import NetworkXError
  from autogluon.common import space
  from autogluon.common.utils.simulation_utils import convert_simulation_artifacts_to_tabular_predictions_dict
  from autogluon.core.constants import BINARY, MULTICLASS, PROBLEM_TYPES_CLASSIFICATION, QUANTILE, REGRESSION
  from autogluon.core.utils import download, unzip
  from autogluon.tabular import TabularDataset, TabularPredictor
  from autogluon.tabular.configs.hyperparameter_configs import get_hyperparameter_config
label_desc: Use image node_id 3 for calling a global function with example usage: _assert_predict_proba_dict_identical_to_predict_proba(predictor, data) without return types