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View Code? Open in Web Editor NEWマディさんとケビンさんの implementation of StyleGAN.
License: MIT License
マディさんとケビンさんの implementation of StyleGAN.
License: MIT License
After #2 is done, experiment with controllable generation so we can select what kind of digit we want to see.
One common problem people encounter when training GANs is that the discriminator gets too good too fast because its task is much easier than the generator's. Did we notice that in the course of our experiments?
Write a GAN that generates handwritten digits.
Even with just the unconditional GAN.
It's hard to evaluate to the performance of a GAN. How do you even do so? Look into the literature to see what kind of stuff they're doing and why they work.
Use TensorBoard from torch.utils.tensorboard
to track the progress of the discriminator to make sure that it doesn't suddenly spike.
Create an animation of the generator output as we interpolate from 0 to 1, 1 to 2, ..., all the way back to 0.
ssh -YC -L 16007:127.0.0.1:6007 workstation
Allows me to access the remote Tensorboard session from http://localhost:16007/
The current idea with conditional generation is to pass in a one-hot vector and use that to determine what kind of number the neural network will generate. What if we wanted to pass in multiple 1's in that vector?
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