code: def validate_model_analysis(
      model_analysis,
      train_data,
      test_data,
      target_column,
      task_type,
      categorical_features,
  ):
      pd.testing.assert_frame_equal(model_analysis.train, train_data)
      pd.testing.assert_frame_equal(model_analysis.test, test_data)
      assert model_analysis.target_column == target_column
      assert model_analysis.task_type == task_type
      assert model_analysis.categorical_features == (
          categorical_features or []
      )
      assert type(model_analysis.categorical_features) is list
      if task_type == ModelTask.CLASSIFICATION:
          classes = train_data[target_column].unique()
          classes.sort()
          np.testing.assert_array_equal(
              model_analysis.rai_insights._classes, classes
          )
  
imports: import os
  from pathlib import Path
  from tempfile import TemporaryDirectory
  import numpy
  import pandas
  import pytest
  from tests.causal_manager_validator import validate_causal
  from tests.common_utils import create_iris_data
  from tests.counterfactual_manager_validator import validate_counterfactual
  from tests.error_analysis_validator import setup_error_analysis, validate_error_analysis
  from tests.explainer_manager_validator import setup_explainer, validate_explainer
  from rai_test_utils.datasets.tabular import create_binary_classification_dataset, create_cancer_data, create_housing_data
  from rai_test_utils.models.model_utils import create_models_classification, create_models_regression
  from rai_test_utils.models.sklearn import create_complex_classification_pipeline
  from rai_test_utils.utilities import is_valid_uuid
  from raiutils.models import ModelTask
  from responsibleai import ModelAnalysis
  from responsibleai._internal.constants import ManagerNames
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
label_desc: Use image node_id 3 for calling a global function with example usage: validate_model_analysis(model_analysis, train_data, test_data, target_column, task_type, categorical_features) without return types