662eff0303e51ff5b60c60c49b03feed2e03d6bb,pytorch/models/nasnet.py,CellStem1,forward,#CellStem1#Any#Any#,537

Before Change

        x_right = self.path(x_prev)

        x_comb0_left = self.comb0_left(x_left)
        x_comb0_right = self.comb0_right(x_right)
        x_comb0 = x_comb0_left + x_comb0_right

        x_comb1_left = self.comb1_left(x_left)
        x_comb1_right = self.comb1_right(x_right)
        x_comb1 = x_comb1_left + x_comb1_right

        x_comb2_left = self.comb2_left(x_left)
        x_comb2_right = self.comb2_right(x_right)
        x_comb2 = x_comb2_left + x_comb2_right

        x_comb3_right = self.comb3_right(x_comb0)
        x_comb3 = x_comb3_right + x_comb1

        x_comb4_left = self.comb4_left(x_comb0)
        x_comb4_right = self.comb4_right(x_left)
        x_comb4 = x_comb4_left + x_comb4_right

        x_out = torch.cat([x_comb1, x_comb2, x_comb3, x_comb4], 1)
        return x_out


class FirstCell(nn.Module):

After Change

    def forward(self, x, _):
        x_left = self.conv1x1(x)
        x_right = x

        x0 = self.comb0_left(x_left) + self.comb0_right(x_right)
        x1 = self.comb1_left(x_left) + self.comb1_right(x_right)
        x2 = self.comb2_left(x_left) + self.comb2_right(x_right)
        x3 = x1 + self.comb3_right(x0)
        x4 = self.comb4_left(x0) + self.comb4_right(x_left)

        x_out = torch.cat((x1, x2, x3, x4), dim=1)
        return x_out, x


class Stem1Unit(nn.Module):

Instances