code: def test_check_consistent_shape(self):
      X_train, X_test, y_train, y_test = generate_data(
          n_train=self.n_train,
          n_test=self.n_test,
          contamination=self.contamination,
      )
  
      (
          X_train_n,
          y_train_n,
          X_test_n,
          y_test_n,
          y_train_pred_n,
          y_test_pred_n,
      ) = check_consistent_shape(
          X_train, y_train, X_test, y_test, y_train, y_test
      )
  
      assert_allclose(X_train_n, X_train)
      assert_allclose(y_train_n, y_train)
      assert_allclose(X_test_n, X_test)
      assert_allclose(y_test_n, y_test)
      assert_allclose(y_train_pred_n, y_train)
      assert_allclose(y_test_pred_n, y_test)
  
      # test shape difference
      with assert_raises(ValueError):
          check_consistent_shape(
              X_train, y_train, y_train, y_test, y_train, y_test
          )
  
      # test shape difference between X_train and X_test
      X_test = np.hstack(
          (X_test, np.zeros((X_test.shape[0], 1)))
      )  # add extra column/feature
      with assert_raises(ValueError):
          check_consistent_shape(
              X_train,
              y_train,
              X_test,
              y_test,
              y_train_pred_n,
              y_test_pred_n,
          )
  
imports: from __future__ import division
  from __future__ import print_function
  import os
  import sys
  import unittest
  import numpy
  from numpy.testing import assert_allclose
  from numpy.testing import assert_equal
  from numpy.testing import assert_raises
  from pyod.utils.data import generate_data_categorical
  from pyod.utils.data import generate_data
  from pyod.utils.data import evaluate_print
  from pyod.utils.data import get_outliers_inliers
  from pyod.utils.data import check_consistent_shape
  from pyod.utils.data import generate_data_clusters
label_desc: Use image node_id 16 for calling the TestData obj's underlying member method code with example usage: obj.test_check_consistent_shape() without return types