def _get_individual_field_tensor_search_terms(self, marqo_query: MarqoTensorQuery) -> List[str]:
        """
        Returns list of strings representing the tensor search terms for each field in the query.
        """
        if isinstance(marqo_query, MarqoHybridQuery):
            searchable_attributes = marqo_query.hybrid_parameters.searchableAttributesTensor
        else:
            searchable_attributes = marqo_query.searchable_attributes

        if searchable_attributes is not None:
            fields_to_search = [f for f in searchable_attributes if f in self._marqo_index.tensor_field_map]
        else:
            fields_to_search = self._marqo_index.tensor_field_map.keys()


        if marqo_query.rerank_depth_tensor is not None:
            rerank_depth = max(marqo_query.rerank_depth_tensor, marqo_query.limit + marqo_query.offset)
        else:
            rerank_depth = marqo_query.limit + marqo_query.offset

        if marqo_query.ef_search is not None:
            rerank_depth = min(rerank_depth, marqo_query.ef_search)
        else:
            # efSearch must be min result_count + offset
            marqo_query.ef_search = max(
                utils.read_env_vars_and_defaults_ints(EnvVars.MARQO_DEFAULT_EF_SEARCH),
                marqo_query.limit + marqo_query.offset
            )
        additional_hits = max(marqo_query.ef_search - rerank_depth, 0)

        terms = []
        for field in fields_to_search:
            tensor_field = self._marqo_index.tensor_field_map[field]
            embedding_field_name = tensor_field.embeddings_field_name
            terms.append(
                f'('
                f'{{'
                f'targetHits:{rerank_depth}, '
                f'approximate:{str(marqo_query.approximate)}, '
                f'hnsw.exploreAdditionalHits:{additional_hits}'
                f'}}'
                f'nearestNeighbor({embedding_field_name}, {common.QUERY_INPUT_EMBEDDING})'
                f')'
            )
        return terms

        Returns list of strings representing the tensor search terms for each field in the query.
        
src/marqo/core/structured_vespa_index/structured_vespa_index.py