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Type annotations for Approximations #258 #322

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manel1874
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@manel1874 manel1874 commented Feb 2, 2022 •
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Description

Added type annotations to the approximations module of SyMPC:

  • exponential.py
  • log.py
  • reciprocal.py
  • sigmoid.py
  • softmax.py
  • tanh.py
  • utils.py

This fixes #258.

Affected Dependencies

None.

How has this been tested?

  • Tested each function individually in a jupyter notebook.

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@gmuraru
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gmuraru commented Feb 6, 2022

Hello @manel1874.
Thank you for the PR - I have some suggestions. Probably you will encounter the circular import problem if you import the MPCTensor.

One solution for this will be to create a register decorator that will keep track of all the approximations we have - something like:

@register_approximation("log")
def log(....)

And this decorator will add the functions in a dictionary.

Then in the MPCTensor we will import a wrapper class around that dictionary and use that to call the approximations.

Let me know if this sounds ok - also if you have more questions - feel free to message me on Slack.

@manel1874
src/sympc/tensor/register_approximations.py: Created a register decor…
1d36c25 
…ator that keeps track of the approximations we have.
gmuraru
gmuraru approved these changes Apr 18, 2022
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LGTM! Nice job!

@gmuraru
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gmuraru commented Apr 18, 2022

@manel1874 could you do a rebase? there was a problem with the black code format tool, but it should be solved now.

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@gmuraru gmuraru gmuraru approved these changes

@aanurraj aanurraj Awaiting requested review from aanurraj aanurraj is a code owner

@kamathhrishi kamathhrishi Awaiting requested review from kamathhrishi kamathhrishi is a code owner

@rasswanth-s rasswanth-s Awaiting requested review from rasswanth-s rasswanth-s is a code owner

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Type annotations for Approximations
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@manel1874 @gmuraru