FIX Return invalid dtype when MPC is applied #4035
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created benchmark folder, and scripts and benchmark graph
Codecov Report
@@ Coverage Diff @@
## master #4035 +/- ##
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- Coverage 94.78% 94.76% -0.02%
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Files 205 205
Lines 21182 21183 +1
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- Hits 20077 20075 -2
- Misses 1105 1108 +3
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gmuraru
approved these changes
Aug 20, 2020
Syzygianinfern0
approved these changes
Aug 22, 2020
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LGTM 🎉
Thank you for your contributions @aanurraj
Well explained solution too 🥳
rav1kantsingh
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to rav1kantsingh/PySyft
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Oct 29, 2020
* added sigmoid_approximation_plot created benchmark folder, and scripts and benchmark graph * added comments * Lint, format, and type-check error fixed * issues fixed * fixed-invalid-dtype-issue * bugs-fixed
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Description
Issue:
this was the original issue #3982 raised there was a mismatch in dtype after using the share()
Reason:
The create_wrapper class which was used to create the wrapper was returning tensor with a dtype torch.float32.
Fix
sending the
type=self.dtypeas a parameter inshared_tensor.wrap()from theshare()solves the issue.wrap()function calls another functionsy.framework.hook.create_wrapper(type, **kwargs)which is appended belowin
create_wrapper(cls, wrapper_type)function if wrapper_type is None we gettorch.Tensor()in return which is by default of dtypetorch.float32(which is our issue). This was easily fixed by sending the dtype from theshare()fucntion which ultimatly reaches tocreate_wrapper(cls, wrapper_type)and sets the dtype.This pull request closes #3982
Affected Dependencies
None
How has this been tested?
one new test case has been added in
test_share_get()function of thetest_additive_shared.pyfile.Checklist