code: def test_batch_only_properties_calculation_with_single_samples_onnx():
      # Arrange
      text = ["Explicit is better than implicit"]
  
      # Act
      properties, properties_types = calculate_builtin_properties(
          raw_text=text,
          batch_size=1,
          include_properties=[
              "Formality",
              "Text Length",
              "Toxicity",
              "Fluency",
          ],
          use_onnx_models=True,
      )
  
      # Assert
      assert_that(
          properties,
          has_entries(
              {
                  "Formality": contains_exactly(close_to(0.955, 0.01)),
                  "Toxicity": contains_exactly(close_to(0.01, 0.01)),
                  "Fluency": contains_exactly(close_to(0.96, 0.01)),
                  "Text Length": contains_exactly(
                      *[len(it) for it in text]
                  ),
              }
          ),
      )
  
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 27 for calling a global function with example usage: test_batch_only_properties_calculation_with_single_samples_onnx() without return types