78eba7b3f82b8420deac3cd28318dbfead0f9b9e,python/baseline/pytorch/seq2seq/model.py,Seq2SeqModel,encode,#Seq2SeqModel#Any#Any#,160

Before Change

    def encode(self, input, src_len):
        embed_in_seq = self.embed(input)
        //if self.training:
        packed = torch.nn.utils.rnn.pack_padded_sequence(embed_in_seq, src_len.data.tolist())
        output_tbh, hidden = self.encoder_rnn(packed)
        output_tbh, _ = torch.nn.utils.rnn.pad_packed_sequence(output_tbh)
        //else:
        //    output_tbh, hidden = self.encoder_rnn(embed_in_seq)

After Change

            tensor = tensor[perm_idx]
            example[key] = tensor

            if self.gpu:
                example[key] = example[key].cuda()

        if "tgt" in batch_dict:
            tgt = torch.from_numpy(batch_dict["tgt"])

Instances