def forward(self, word, sentence_length):
    '\n        :param word:\n        :param sentence_length:\n        :param desorted_indices:\n        :return:\n        '
    (word, sentence_length, desorted_indices) = prepare_pack_padded_sequence(word, sentence_length, device=self.device)
    x = self.embed(word)
    x = self.dropout_embed(x)
    packed_embed = pack_padded_sequence(x, sentence_length, batch_first=True)
    (x, _) = self.bilstm(packed_embed)
    (x, _) = pad_packed_sequence(x, batch_first=True)
    x = x[desorted_indices]
    x = self.dropout(x)
    x = torch.tanh(x)
    logit = self.linear(x)
    return logit
:param word:
:param sentence_length:
:param desorted_indices:
:return:
def forward(self, word, sentence_length):
    '\n        :param word:\n        :param sentence_length:\n        :param desorted_indices:\n        :return:\n        '
    (word, sentence_length, desorted_indices) = prepare_pack_padded_sequence(word, sentence_length, device=self.device)
    x = self.embed(word)
    x = self.dropout_embed(x)
    packed_embed = pack_padded_sequence(x, sentence_length, batch_first=True)
    (x, _) = self.bilstm(packed_embed)
    (x, _) = pad_packed_sequence(x, batch_first=True)
    x = x[desorted_indices]
    x = self.dropout(x)
    x = torch.tanh(x)
    logit = self.linear(x)
    return logit