9ea14875825b2ab63a43ad2f0f5159d99df86d02,model.py,Lookahead,forward,#Lookahead#Any#,122

Before Change

        self.weight.uniform_(-stdv, stdv)

    def forward(self, input):
        seq_len = input.size(0)
        // pad the 0th dimension (T/sequence) with zeroes whose number = context
        // Once pytorch"s padding functions have settled, should move to those.
        padding = torch.zeros(self.context, *(input.size()[1:])).type_as(input)
        x = torch.cat((input, padding), 0)

After Change

    def forward(self, x):
        x = x.transpose(0, 1).transpose(1, 2)
        x = F.pad(x, pad=self.pad, value=0)
        x = self.conv(x)
        x = x.transpose(1, 2).transpose(0, 1).contiguous()
        return x

    def __repr__(self):
        return self.__class__.__name__ + "(" \

Instances