gaurav-arya / StochasticAD.jl

Research package for automatic differentiation of programs containing discrete randomness.
MIT License
198 stars 16 forks source link

Add stochastic triple smoothing backend #81

Closed gaurav-arya closed 1 year ago

gaurav-arya commented 1 year ago

TODO:

codecov-commenter commented 1 year ago

Codecov Report

Patch coverage: 96.19% and project coverage change: +0.84 :tada:

Comparison is base (8a67258) 89.49% compared to head (1a85493) 90.33%.

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Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #81 +/- ## ========================================== + Coverage 89.49% 90.33% +0.84% ========================================== Files 12 12 Lines 571 621 +50 ========================================== + Hits 511 561 +50 Misses 60 60 ``` | [Impacted Files](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya) | Coverage Δ | | |---|---|---| | [src/finite\_infinitesimals.jl](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya#diff-c3JjL2Zpbml0ZV9pbmZpbml0ZXNpbWFscy5qbA==) | `100.00% <ø> (ø)` | | | [src/backends/smoothed.jl](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya#diff-c3JjL2JhY2tlbmRzL3Ntb290aGVkLmps) | `86.48% <87.87%> (+4.66%)` | :arrow_up: | | [src/backends/dict.jl](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya#diff-c3JjL2JhY2tlbmRzL2RpY3Quamw=) | `92.06% <100.00%> (ø)` | | | [src/backends/pruned.jl](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya#diff-c3JjL2JhY2tlbmRzL3BydW5lZC5qbA==) | `91.30% <100.00%> (ø)` | | | [src/backends/pruned\_aggressive.jl](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya#diff-c3JjL2JhY2tlbmRzL3BydW5lZF9hZ2dyZXNzaXZlLmps) | `91.07% <100.00%> (ø)` | | | [src/discrete\_randomness.jl](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya#diff-c3JjL2Rpc2NyZXRlX3JhbmRvbW5lc3Muamw=) | `97.29% <100.00%> (+3.17%)` | :arrow_up: | | [src/general\_rules.jl](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya#diff-c3JjL2dlbmVyYWxfcnVsZXMuamw=) | `93.85% <100.00%> (+1.07%)` | :arrow_up: | | [src/propagate.jl](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya#diff-c3JjL3Byb3BhZ2F0ZS5qbA==) | `85.00% <100.00%> (ø)` | | | [src/smoothing.jl](https://codecov.io/gh/gaurav-arya/StochasticAD.jl/pull/81?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya#diff-c3JjL3Ntb290aGluZy5qbA==) | `90.47% <100.00%> (-0.44%)` | :arrow_down: | Help us with your feedback. Take ten seconds to tell us [how you rate us](https://about.codecov.io/nps?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya). Have a feature suggestion? [Share it here.](https://app.codecov.io/gh/feedback/?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Gaurav+Arya)

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