(self, sentences: List[List[str]])
Parameters
        ----------
        sentences: List[List[str]]
            A batch of sentences. len(sentences) is the batch size, and each sentence
            itself is a list of strings (the constituent words).

        Returns
        -------
        representations: List[FloatTensor]
            A list with the contextualized representations of all words in an input
            sentence. Each inner FloatTensor is of shape (num_layers, seq_len, repr_dim)
            indicating the number of layers of represntations to evaluate, the length
            of the sentence, and the dimensionality of each contextualized word representation,
            respectively.
Parameters
        ----------
        sentences: List[List[str]]
            A batch of sentences. len(sentences) is the batch size, and each sentence
            itself is a list of strings (the constituent words).
Parameters ---------- sentences : List [ List [ str ]] A batch of sentences . len ( sentences ) is the batch size and each sentence itself is a list of strings ( the constituent words ) .
def forward(self, sentences: List[List[str]]) -> torch.FloatTensor:
        """
        Parameters
        ----------
        sentences: List[List[str]]
            A batch of sentences. len(sentences) is the batch size, and each sentence
            itself is a list of strings (the constituent words).

        Returns
        -------
        representations: List[FloatTensor]
            A list with the contextualized representations of all words in an input
            sentence. Each inner FloatTensor is of shape (num_layers, seq_len, repr_dim)
            indicating the number of layers of represntations to evaluate, the length
            of the sentence, and the dimensionality of each contextualized word representation,
            respectively.
        """
        raise NotImplementedError
def forward ( self , sentences : List [ List [ str ] ] ) -> torch . FloatTensor : raise NotImplementedError