def test_open_clip_encode_text_normalized(self):
        """
        A test to ensure that the open clip model generates the same embeddings as the pipeline for text inputs when
        normalize is set to True.
        """
        texts = ['hello', 'big', 'asasasasaaaaaaaaaaaa', '', 'a word. another one!?. #$#.']

        tokenized_text = self.model.get_preprocessor().preprocess(texts, modality=Modality.TEXT)
        raw_embeddings = self.model.encode(tokenized_text, modality=Modality.TEXT, normalize=True)
        pipeline_embeddings = self.encode_content_helper(
            content=texts,
            model_name=self.model_name,
            modality=Modality.TEXT,
            device=self.device,
            normalize_embeddings=True
        )

        for i, raw_embedding in enumerate(raw_embeddings):
            pipeline_embedding = pipeline_embeddings[i]
            self.assertEqual(raw_embedding.shape, pipeline_embedding.shape)
            self.assertTrue((raw_embedding - pipeline_embedding < self.eps).all())
            self.assertEqual(raw_embedding.shape[0], self.model.model_properties.dimensions)
            self.validate_norm(raw_embedding, epsilon=self.eps, normalize=True)
            self.validate_norm(pipeline_embedding, epsilon=self.eps, normalize=True)

        A test to ensure that the open clip model generates the same embeddings as the pipeline for text inputs when
        normalize is set to True.
        
tests/integ_tests/inference/native_inference/embedding_models/test_open_clip_model_encode.py