code: def test_batch_size_change(tweet_emotion_train_test_textdata):
      # Arrange
      _, test = tweet_emotion_train_test_textdata
      test_text = test.text
      batch_sizes = [1, 8, 16, 32, 64]
  
      # Act
      for batch in batch_sizes:
          result = calculate_builtin_properties(
              test_text,
              include_properties=[
                  "Average Words Per Sentence",
                  "Unique Noun Count",
              ],
              batch_size=batch,
          )[0]
          result_none_text = calculate_builtin_properties(
              [None],
              include_properties=[
                  "Average Words Per Sentence",
                  "Unique Noun Count",
              ],
              batch_size=batch,
          )[0]
  
          # Assert
          assert_that(
              result["Average Words Per Sentence"][0:10],
              equal_to(
                  [
                      5.667,
                      7.0,
                      11.0,
                      12.0,
                      8.0,
                      19.0,
                      3.0,
                      9.0,
                      11.5,
                      7.333,
                  ]
              ),
          )
          assert_that(
              result["Unique Noun Count"][0:10],
              equal_to([9, 2, 3, 3, 4, 10, np.nan, 2, 7, 5]),
          )
          assert_that(
              result_none_text["Average Words Per Sentence"],
              equal_to([np.nan]),
          )
          assert_that(
              result_none_text["Unique Noun Count"], equal_to([np.nan])
          )
  
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 11 for calling a global function with example usage: test_batch_size_change(tweet_emotion_train_test_textdata) without return types