Understanding the ResnetGenerator in the CycleGan Model

In their famous research paper on CycleGans, the authors implement – well, a CycleGan.

There are two discriminators and two generators for the CycleGan. Now, they also provide their neural networks code. I am particularly interested in the generator(s), which they implement here:

So they use a ResnetGenerator, but I’m afraid I do not really understand it yet (cf. lines 119-159 and 315-373).

For the generator, why do we have both downsampling (Conv2d) and upsampling (ConvTranpose2d) layers? I generally know it like this for the generator that the generator only uses ConvTranpose2d layers, where the input is noise sampled from a uniform or Gaussian distribution..

That’s why I am confused..