langchain/embeddings/tensorflow_hub.py/TensorflowHubEmbeddings/embed_documents
class TensorflowHubEmbeddings:    def embed_documents(self, texts: List[str]) -> List[List[float]]:
        """Compute doc embeddings using a TensorflowHub embedding model.

        Args:
            texts: The list of texts to embed.

        Returns:
            List of embeddings, one for each text.
        """
        texts = list(map(lambda x: x.replace("\n", " "), texts))
        embeddings = self.embed(texts).numpy()
        return embeddings.tolist()