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Automatic clipping #798
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Automatic clipping #798
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Hi @ParthS007! Thank you for your pull request and welcome to our community. Action RequiredIn order to merge any pull request (code, docs, etc.), we require contributors to sign our Contributor License Agreement, and we don't seem to have one on file for you. ProcessIn order for us to review and merge your suggested changes, please sign at https://code.facebook.com/cla. If you are contributing on behalf of someone else (eg your employer), the individual CLA may not be sufficient and your employer may need to sign the corporate CLA. Once the CLA is signed, our tooling will perform checks and validations. Afterwards, the pull request will be tagged with If you have received this in error or have any questions, please contact us at cla@meta.com. Thanks! |
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Thank you for signing our Contributor License Agreement. We can now accept your code for this (and any) Meta Open Source project. Thanks! |
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Request for review: @EnayatUllah |
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Hi Parth, thank you for your contribution, I have initiated testing. |
Pull Request Test Coverage Report for Build 18935495756Warning: This coverage report may be inaccurate.This pull request's base commit is no longer the HEAD commit of its target branch. This means it includes changes from outside the original pull request, including, potentially, unrelated coverage changes.
Details
💛 - Coveralls |
…utomaticClippingOptimizer
… get_optimizer_class less complex (flake8 error fix)
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@facebook-github-bot has imported this pull request. If you are a Meta employee, you can view this in D87577954. (Because this pull request was imported automatically, there will not be any future comments.) |
Types of changes
Motivation and Context / Related issue
Implements automatic clipping optimizers based on the paper "Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger" (https://arxiv.org/pdf/2206.07136).
Fixes #797
How Has This Been Tested (if it applies)
opacus/tests/automatic_clipping.py(3 tests, all passing)opacus/tests/multigpu_automatic_clipping_test.pyclipping="automatic"andclipping="automatic_per_layer"modesChecklist