def test_imageIndexEmbeddingsUnnormalised(self):
        """Test to ensure that the image embeddings are unnormalised when the index is unnormalised"""
        documents = [
            {
                "image_field_1": TestImageUrls.HIPPO_REALISTIC.value,
                "_id": "1"
            }
        ]
        for index_name in [self.unstructured_image_index_unnormalized_name, self.structured_image_index_unnormalized_name]:
            tensor_fields = ["image_field_1"] if index_name == self.unstructured_image_index_unnormalized_name \
                else None
            with self.subTest(index_name):
                res = self.add_documents(
                    self.config,
                    add_docs_params=AddDocsParams(
                        docs=documents,
                        index_name=index_name,
                        tensor_fields=tensor_fields
                    )
                )
                for item in res.dict(exclude_none=True, by_alias=True)['items']:
                    self.assertEqual(200, item['status'])

                get_res = tensor_search.get_documents_by_ids(
                    config=self.config, index_name=index_name,
                    document_ids=["1"],
                    show_vectors=True
                ).dict(exclude_none=True, by_alias=True)

                embeddings = get_res['results'][0]['_tensor_facets'][0]['_embedding']
                norm = np.linalg.norm(np.array(embeddings))
                self.assertTrue(norm - 1.0 > 1e-5, f"Embedding norm is {norm}")
Test to ensure that the image embeddings are unnormalised when the index is unnormalised
tests/integ_tests/tensor_search/integ_tests/test_add_documents_combined.py