Implement Generative Adversarial Networks (GANs)

Adversarial-Deep-Learning / code-soup

This is a collection of algorithms and approaches used in the book adversarial deep learning

MIT License

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Implement Generative Adversarial Networks (GANs) #1

Closed someshsingh22 closed 3 years ago

someshsingh22 commented 3 years ago

@Adversarial-Deep-Learning/core-dev

https://papers.nips.cc/paper/2014/file/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf

[X] Dataset Class
[x] Unit Test Cases
[X] Utils
[X] Core components (Generator / Discriminator)
[X] Training
[x] Linting Failures
[x] Remove Dummy Files
[x] Make Algorithm Modular
[x] #21
[x] Shift functional code outside coverage
[x] #24
[x] #22

someshsingh22 commented 3 years ago

@blackrosedragon2 Final Linting report shows some errors, you can check them here https://github.com/Adversarial-Deep-Learning/code-soup/runs/3268983541 make the changes in a new PR and we will close this

Also init.py file is missing from chapter, you can take a look at the latest PR #9 to see how tests and modules can be built or called

Once built you can remove the dummy files

someshsingh22 commented 3 years ago

@blackrosedragon2 check the coverage report we have to get maximum coverage, all functions that need time like training will be ignored only structural and functional requirements should be checked.

someshsingh22 commented 3 years ago

The remaining issues are left open to avoid clutter in this Issue