Computes the ELMo embeddings for a iterable of sentences.

        Please note that ELMo has internal state and will give different results for the same input.
        See the comment under the class definition.

        Parameters
        ----------
        sentences : ``Iterable[List[str]]``, required
            An iterable of tokenized sentences.
        batch_size : ``int``, required
            The number of sentences ELMo should process at once.

        Returns
        -------
            A list of tensors, each representing the ELMo vectors for the input sentence at the same index.

def embed_sentences(self,
                        sentences: Iterable[List[str]],
                        batch_size: int = DEFAULT_BATCH_SIZE) -> Iterable[numpy.ndarray]:
        """
        Computes the ELMo embeddings for a iterable of sentences.

        Please note that ELMo has internal state and will give different results for the same input.
        See the comment under the class definition.

        Parameters
        ----------
        sentences : ``Iterable[List[str]]``, required
            An iterable of tokenized sentences.
        batch_size : ``int``, required
            The number of sentences ELMo should process at once.

        Returns
        -------
            A list of tensors, each representing the ELMo vectors for the input sentence at the same index.
        """
        for batch in lazy_groups_of(iter(sentences), batch_size):
            yield from self.embed_batch(batch)