Generator and discriminator loss curves are exact mirror images

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Generator and discriminator loss curves are exact mirror images



I am currently training a GAN using Pytorch to produce histopathology data for my research. I am using BCE criterion for both Generator and Discriminator. The network is able to produce good quality images but the loss curves are bit mysterious for me.
The generator and discriminator loss curves look like exact mirror images. See the attached tensor-board snip. Can someone tell me why this is happening?



Edit 1: Both generator and discriminator loss curves should show convergence, right?



Thanks a lot in advance!
enter image description here




1 Answer
1



The training curve you produce is somehow standard when training a GAN. The Generator and Discriminator are going to converge. If you plot the Gen Loss and Dis Loss together, you'll find out adversarial property. In fact, most of the time, validating the model by looking at the generated image is an efficient way.
Here are some of my works for your reference.






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