Some implementation details about the official code

[Haosouth]

Thank you very much for implementing swappingGAN in a very concise way. I believe you have a deep understanding of the official code. I am trying to understand the official code implementation, but I have encountered difficulties in some codes and cannot be solved. 1. I learned that the optimizer uses swapping_autoencoder_optimizer by default. This class uses a def prepare_images(data_i), but only returns data_i['real_A'], which does not seem to use 'real_B'. 2. In the subsequent self.E(real) process, sp and gl are output, and their mix=self.G(self.swap(sp),gl), why does the sp and gl used by mix come from the same sheet Image, shouldn't it be from real_A and real_B respectively, and what is the purpose of this self.swap(sp)? The above is my question. I am very sorry to bother you. If you are free, I hope you can answer my doubts. Thank you very much.