b2074ddf9d8bc2069d66976fea58a52f40238496,pretrainedmodels/nasnet.py,CellStem1,forward,#CellStem1#Any#Any#,120

Before Change

        x_left_1 = self.pool_1(x_left)
        x_left_1 = self.conv_1(x_left_1)

        x_left = torch.cat([x_left_0, x_left_1], 1)
        x_left = self.bn_left(x_left)

        x_right = F.relu(x_right)

After Change

        // path 1
        x_path1 = self.path_1(x_relu)
        // path 2
        x_path2 = self.path_2.pad(x_relu)
        x_path2 = x_path2[:, :, 1:, 1:]
        x_path2 = self.path_2.avgpool(x_path2)
        x_path2 = self.path_2.conv(x_path2)
        // final path
        x_right = self.final_path_bn(torch.cat([x_path1, x_path2], 1))

        x_comb_iter_0_left = self.comb_iter_0_left(x_left)
        x_comb_iter_0_right = self.comb_iter_0_right(x_right)
        x_comb_iter_0 = x_comb_iter_0_left + x_comb_iter_0_right

        x_comb_iter_1_left = self.comb_iter_1_left(x_left)
        x_comb_iter_1_right = self.comb_iter_1_right(x_right)
        x_comb_iter_1 = x_comb_iter_1_left + x_comb_iter_1_right

        x_comb_iter_2_left = self.comb_iter_2_left(x_left)
        x_comb_iter_2_right = self.comb_iter_2_right(x_right)
        x_comb_iter_2 = x_comb_iter_2_left + x_comb_iter_2_right

        x_comb_iter_3_right = self.comb_iter_3_right(x_comb_iter_0)
        x_comb_iter_3 = x_comb_iter_3_right + x_comb_iter_1

        x_comb_iter_4_left = self.comb_iter_4_left(x_comb_iter_0)
        x_comb_iter_4_right = self.comb_iter_4_right(x_left)
        x_comb_iter_4 = x_comb_iter_4_left + x_comb_iter_4_right

        x_out = torch.cat([x_comb_iter_1, x_comb_iter_2, x_comb_iter_3, x_comb_iter_4], 1)
        return x_out


class FirstCell(nn.Module):
    

Instances