We're into the final week of Phase I and, thanks to Marcus' suggestions and reviews, right on track! A number of key decisions were taken up by us this week.
GAN code is finally ready to get merged, and the
DCGAN code has been pushed, which should be ready to get merged by the end of this week. As discussed with Marcus, the
DCGAN code uses the same class as the standard
GAN, which allows us the freedom to just implement the test cases, as the required layers are already available in
This week we got some good results with the
GAN code on a 500-image subset of
MNIST dataset, and I'm currently in process of running the code on the full 70,000-image
MNIST dataset, which would be posted in the PR itself. Also, we decided to not run the test on
Travis, and instead, push the code to the
mlpack/models repository, whch would be done soon.
Also, we decided to try out optimizer separation and implementing batch support for the
GAN implementation after Phase I, which would allow us flexibility to compare and contrast our single optimizer output as well, and provide full user flexibility to try out different variants of the
That's all for now! See you next week!
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