31e7f40c3381aac21e8665d0b5706bceddd9de94,onmt/Models.py,Decoder,forward,#Decoder#Any#Any#Any#Any#Any#,334

Before Change

        emb = self.word_lut(input)
        if self.positional_encoding:
            emb = emb + Variable(self.pe[:emb.size(0), :1, :emb.size(2)].expand_as(emb))
            emb = emb * math.sqrt(emb.size(2))
            
        // n.b. you can increase performance if you compute W_ih * x for all
        // iterations in parallel, but that"s only possible if
        // self.input_feed=False

After Change

            if False:
                if hidden:
                    outputs = outputs[hidden.size(0):]
                    attn = attn[:, hidden.size(0):].squeeze()
                    attn = torch.stack([attn])
                
            attns["std"] = attn
            if self._copy:

Instances