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increase Parity threshold (#4795) 

* increase Parity threshold

* typos

* increase

* increase
This commit is contained in:
Jirka Borovec 2020-11-20 20:58:45 +01:00 committed by GitHub
parent 94a9d3d283
commit 500e2853f3
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2 changed files with 5 additions and 4 deletions
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6
.github/PULL_REQUEST_TEMPLATE.md vendored
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@ -19,15 +19,15 @@ Fixes # (issue)
- [ ] Did you verify new and existing tests pass locally with your changes?
- [ ] If you made a notable change (that affects users), did you update the [CHANGELOG](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/CHANGELOG.md)?
<!-- For CHANGELOG separate each item in unreleased section by a blank line to reduce collisions -->
<!-- For CHANGELOG separate each item in the unreleased section by a blank line to reduce collisions -->
## PR review
Anyone in the community is free to review the PR once the tests have passed.
Before you start reviewing make sure you have read [Review guidelines](https://github.com/PyTorchLightning/pytorch-lightning/wiki/Review-guidelines). In in short, see following bullet-list:
Before you start reviewing make sure you have read [Review guidelines](https://github.com/PyTorchLightning/pytorch-lightning/wiki/Review-guidelines). In short, see the following bullet-list:
- [ ] Is this pull request ready for review? (if not, please submit in draft mode)
- [ ] Check that all items from **Before submitting** are resolved
- [ ] Make sure the title is self explanatory and the description concisely explains the PR
- [ ] Make sure the title is self-explanatory and the description concisely explains the PR
- [ ] Add labels and milestones (and optionally projects) to the PR so it can be classified; _Bugfixes should be including in bug-fix release milestones (m.f.X) and features should be included in (m.X.b) releases._

3
benchmarks/test_parity.py
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@ -9,9 +9,10 @@ from pytorch_lightning import Trainer, seed_everything
from tests.base.models import ParityModuleMNIST, ParityModuleRNN
# TODO: explore where the time leak comes from
@pytest.mark.parametrize('cls_model,max_diff', [
(ParityModuleRNN, 0.05),
(ParityModuleMNIST, 0.82)
(ParityModuleMNIST, 0.99)
])
@pytest.mark.skipif(not torch.cuda.is_available(), reason="test requires GPU machine")
def test_pytorch_parity(tmpdir, cls_model, max_diff):