Dropout used in paper?

[JohnGiorgi]

Hi,

I am just wondering if you used dropout in your paper? If so, would you mind telling me where the dropout layer was applied and what dropout ratio was used?

Thanks in advance!

[yuzhimanhua]

Hi,

Yes, we use dropout in our model, and its ratio is fixed to 0.5. It is applied in char_emb, char_lstm, word_emb, and word_lstm. You can also refer to our forward() function.

def forward(self, forw_sentence, forw_position, back_sentence, back_position, word_seq, file_no, hidden=None):

        self.set_batch_seq_size(forw_position)

        #embedding layer
        forw_emb = self.char_embeds(forw_sentence)
        back_emb = self.char_embeds(back_sentence)

        #dropout
        d_f_emb = self.dropout(forw_emb)
        d_b_emb = self.dropout(back_emb)

        #forward the whole sequence
        forw_lstm_out, _ = self.forw_char_lstm(d_f_emb)#seq_len_char * batch * char_hidden_dim

        back_lstm_out, _ = self.back_char_lstm(d_b_emb)#seq_len_char * batch * char_hidden_dim

        #select predict point
        forw_position = forw_position.unsqueeze(2).expand(self.word_seq_length, self.batch_size, self.char_hidden_dim)
        select_forw_lstm_out = torch.gather(forw_lstm_out, 0, forw_position)

        back_position = back_position.unsqueeze(2).expand(self.word_seq_length, self.batch_size, self.char_hidden_dim)
        select_back_lstm_out = torch.gather(back_lstm_out, 0, back_position)

        fb_lstm_out = self.dropout(torch.cat((select_forw_lstm_out, select_back_lstm_out), dim=2))
        if self.if_highway:
            char_out = self.fb2char(fb_lstm_out)
            d_char_out = self.dropout(char_out)
        else:
            d_char_out = fb_lstm_out

        #word
        word_emb = self.word_embeds(word_seq)
        d_word_emb = self.dropout(word_emb)

        #combine
        word_input = torch.cat((d_word_emb, d_char_out), dim = 2)

        #word level lstm
        lstm_out, _ = self.word_lstm(word_input)
        d_lstm_out = self.dropout(lstm_out)

        #convert to crf
        crf_out = self.crflist[file_no](d_lstm_out)
        crf_out = crf_out.view(self.word_seq_length, self.batch_size, self.tagset_size, self.tagset_size)
        
        return crf_out

Thanks!

[JohnGiorgi]

Okay great, thanks for the quick response!