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ptstat's Issues

Code review

Hello!
I found your repo in pytorch discourse. I'm a pymc3 team member. Very happy that Bayes goes to pytorch too. We were planning to investigate if pytorch is suitable for bayesian reasoning. You can read our discussion here. I'd like to leave some comments for future improvements

  • Assertion errors can be hard to catch and if you have one, you can't figure out what type is it. I think some of assertions are not needed as they are checked at runtime without any supplementary code.

  • Now I see all stuff in code. Hope in future it will be more organized. Distribution submodule with splitting to distribution types can be a good solution.

  • Use pytest. I got used to unittest until tried pytest, now I have no way back to unittest, pytest is awesome

  • Use docstrings instead of # comment. It can be helpfull for future users

  • Remove NormalUnit and Uniform01, add defaults instead. Having lots of classes of the same distribution can be messy

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