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add decorator for flaky tf sparsity tests #65
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mgoin
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Feb 5, 2021
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cool, didn't know about flaky |
markurtz
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Feb 5, 2021
markurtz
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* GA code, toctree links (#61) - added tracking for docs output - added help links for docs output * Update README.md (#64) removed placeholder reference to comingsoon repo in favor of active repo * add decorator for flaky tf sparsity tests (#65) * enable modifier groups in SparseML recipes (#66) * enable modifier groups in SparseML recipes * unit tests for YAML modifier list loading * make build argument for nightly builds (#63) * rst url syntax correction (#67) correcting double slash at the end of URLs with updates to index.rst pre-compilation * match types explicitly in torch qat quant observer wrappers (#68) * docs updates (#71) enhancing left nav for Help; after this merge, the docs need to be rebuilt for this repo so docs.neuralmagic.com can be refreshed. cc @markurtz * Rename KSModifier to PruningModifier (#76) * Rename ConstantKSModifier to ConstantPruningModifier * Rename GradualKSModifier to GMPruningModifier * Fix broken link for Optimization Recipes (#75) * Serialize/deserialize MaskedLayer (#69) * Serialize/deserialize MaskedLayer * Remove unused symbols * Register pruning scheduler classes for serialization * removed ScheduledOptimizer, moved logic to ScheduledModifierManager (#77) * load recipes directly from SparseZoo (#72) * load recipes into Managers from sparsezoo stubs * moving recipe_type handling to SparseZoo only, supporting loading SparseZoo recipe objects * Revert "removed ScheduledOptimizer, moved logic to ScheduledModifierManager (#77)" (#80) This reverts commit 6073abb. * Update for 0.1.1 release (#82) * Update for 0.1.1 release - update python version to 0.1.1 - setup.py add in version parts and _VERSION_MAJOR_MINOR for more flexibility with dependencies between neural magic packages - add in deepsparse optional install pathway * missed updating version to 0.1.1 * rename examples directory to integrations (#78) * rwightman/pytorch-image-models integration (#70) * load checkpoint file based on sparsezoo recipe in pytorch_vision script (#83) * ultralytics/yolov5 integration (#73) * pytorch sparse quantized transfer learning notebook (#81) * load qat onnx models for conversion from file path (#86) * Sparsification update (#84) * Sparsification update - update sparsification descriptions and move to preferred verbage * update from comments on deepsparse for sparsification * Update README.md Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * Update README.md Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * Update README.md Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * Update README.md Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * Update docs/source/index.rst Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * Update docs/source/index.rst Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * Update docs/source/index.rst Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * Update docs/source/index.rst Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * Update docs/source/recipes.md Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * fix links in index.rst from reviewed content * update overviews and taglines from doc Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> * blog style readme for torch sparse-quant TL notebook (#85) Co-authored-by: Jeannie Finks (NM) <74554921+jeanniefinks@users.noreply.github.com> Co-authored-by: Benjamin Fineran <bfineran@users.noreply.github.com> Co-authored-by: Eldar Kurtic <eldar.ciki@gmail.com> Co-authored-by: Tuan Nguyen <tuan@neuralmagic.com>
markurtz
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Some of our tensorflow_v1 sparsity mask tests use randomly initialized tensors for testing. This can cause errors on the unlikely (but not impossible) chance that the randomly initialized tensor has a 0 in it as well as other situations. We've seen this happen less than 5 times over the last 6 months, but it's happened twice in the last week now, so am nipping this in the bud. @kevinaer suggested looking into flaky tests when this first occured.
Adding the flaky decorator, has pytest rerun the flaky test once (can be set to other values) if it fails. This should be greatly decrease the chance that one of these tests will fail due to a 0 popping up in the test tensor.
https://pypi.org/project/flaky/
even though the decorator is called through pytest, I've checked that flaky must be installed for the logic to properly function.