Hi, I am reproducing this work of yours, I had to make some modifications to your code to get it to run due to different hardware drivers. The changes are as follows:
I modified the position of optim_G.step() to move it before optim_D.step().
but I found that I could not reproduce your results. I have examined the code and found that the problem lies in the training of the GAN, I found that following your code when running on my hardware a pattern collapse occurs, i.e. the generator's loss starts close to 0.However discriminator losses are very high. Here the gen_loss and dsc_loss I have recorded using the code shown below:
I would like to ask you if you have encountered this problem in your implementation? If not, can you please spot where my problem occurs?
Hi, it seems there are some issues that are coming from version differences. and another issue seems to have been discussing this. Please refer to issue 6.
Hi, I am reproducing this work of yours, I had to make some modifications to your code to get it to run due to different hardware drivers. The changes are as follows:
but I found that I could not reproduce your results. I have examined the code and found that the problem lies in the training of the GAN, I found that following your code when running on my hardware a pattern collapse occurs, i.e. the generator's loss starts close to 0.However discriminator losses are very high. Here the gen_loss and dsc_loss I have recorded using the code shown below:
I would like to ask you if you have encountered this problem in your implementation? If not, can you please spot where my problem occurs?