code: def test_include_properties():
      # Arrange
      test_text = ["This is simple sentence."]
      # Also check capitalization doesn't matter:
      expected_properties = ["Text Length", "Average Word Length"]
      include_properties = ["Text length", "average Word length"]
  
      # Act
      result = calculate_builtin_properties(
          test_text, include_properties=include_properties
      )[0]
      # Assert
      for prop in result:
          assert_that(expected_properties, has_item(prop))
  
      # Check that raises if include_properties is not a list:
      assert_that(
          calling(calculate_builtin_properties).with_args(
              test_text, include_properties="bla"
          ),
          raises(DeepchecksValueError),
      )
  
      # Check that raises if property doesn't exist:
      assert_that(
          calling(calculate_builtin_properties).with_args(
              test_text, include_properties=["Non Existent Property"]
          ),
          raises(
              DeepchecksValueError,
              r"include_properties contains properties that were not found: \[\'non existent property\'\].",
          ),
      )
  
imports: import os
  import pathlib
  import timeit
  import uuid
  import numpy
  import pytest
  from hamcrest import *
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.nlp.utils.text_properties import TOXICITY_MODEL_NAME_ONNX, _sample_for_property, calculate_builtin_properties, english_text
  from deepchecks.nlp.utils.text_properties_models import MODELS_STORAGE, _get_transformer_model_and_tokenizer
label_desc: Use image node_id 23 for calling a global function with example usage: test_include_properties() without return types