662eff0303e51ff5b60c60c49b03feed2e03d6bb,pytorch/models/nasnet.py,NormalCell,forward,#NormalCell#Any#Any#,672

Before Change

        x_right = self.conv_1x1(x)

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

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

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

        x_comb3_left = self.comb_iter_3_left(x_left)
        x_comb3_right = self.comb3_right(x_left)
        x_comb3 = x_comb3_left + x_comb3_right

        x_comb4_left = self.comb4_left(x_right)
        x_comb4 = x_comb4_left + x_right

        x_out = torch.cat([x_left, x_comb0, x_comb1, x_comb2, x_comb3, x_comb4], 1)
        return x_out


class ReductionCell0(nn.Module):

After Change

        x_left = self.conv1x1(x)
        x_right = self.path(x_prev)

        x0 = self.comb0_left(x_left) + self.comb0_right(x_right)
        x1 = self.comb1_left(x_right) + self.comb1_right(x_right)
        x2 = self.comb2_left(x_left) + x_right
        x3 = self.comb3_left(x_right) + self.comb3_right(x_right)
        x4 = self.comb4_left(x_left) + x_left

        x_out = torch.cat((x_right, x0, x1, x2, x3, x4), dim=1)
        return x_out, x


class NormalUnit(nn.Module):

Instances