def test_split_prefix_preprocess_text_tokenizer_called(self):
        """
        Ensure that the tokenizer wrapper is called when preprocessing text.
        """
        tokenizer_wrapper = MagicMock(spec=MultilingualCLIPTokenizerWrapper)
        tokenizer_wrapper.tokenize.return_value = "tokenized_text"

        model = MagicMock(spec=MultilingualCLIPModel)
        model.get_preprocessor.return_value = tokenizer_wrapper

        inference_request = InferenceRequest(
            modality=Modality.TEXT,
            contents=["This is a test sentence."],
            preprocessing_config=TextPreprocessingConfig(),
            return_individual_error=False,
            model_config=MagicMock(spec=ModelConfig)
        )

        pipeline = MultilingualCLIPModelInferencePipeline(model, inference_request)

        with patch(
                "marqo.inference.native_inference.inference_pipeline.multilingual_inference_pipeline."
                "split_prefix_preprocess_text"
        ) as mock_split:
            mock_split.side_effect = lambda contents, preprocessor, config: [
                [(contents[0], preprocessor.tokenize(contents[0]))]]
            result = pipeline._content_preprocessing()

        tokenizer_wrapper.tokenize.assert_called_once_with("This is a test sentence.")
        self.assertEqual(result[0][0][1], "tokenized_text")

        Ensure that the tokenizer wrapper is called when preprocessing text.
        
tests/unit_tests/marqo/inference/native_inference/test_multiling_clip_inference_pipeline.py