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.azure-pipelines/gpu-tests.yml

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bash pl_examples/run_examples.sh --trainer.gpus=1
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bash pl_examples/run_examples.sh --trainer.gpus=2 --trainer.accelerator=ddp
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bash pl_examples/run_examples.sh --trainer.gpus=2 --trainer.accelerator=ddp --trainer.precision=16
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bash pl_examples/run_examples.sh --trainer.gpus=2 --trainer.accelerator=dp
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bash pl_examples/run_examples.sh --trainer.gpus=2 --trainer.accelerator=dp --trainer.precision=16
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env:
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PL_USE_MOCKED_MNIST: "1"
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displayName: 'Testing: examples'

.codecov.yml

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# https://codecov.readme.io/v1.0/docs/commit-status
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project:
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default:
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against: auto
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target: 99% # specify the target coverage for each commit status
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threshold: 30% # allow this little decrease on project
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# https://github.com/codecov/support/wiki/Filtering-Branches
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# https://github.com/codecov/support/wiki/Patch-Status
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patch:
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default:
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against: auto
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target: 50% # specify the target "X%" coverage to hit
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# threshold: 50% # allow this much decrease on patch
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changes: false
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# https://docs.codecov.com/docs/github-checks#disabling-github-checks-patch-annotations
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github_checks:
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annotations: false
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parsers:
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gcov:
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branch_detection:
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---
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name: Code improvement
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about: Suggest a code improvement, i.e. refactoring, deprecation, etc.
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title: ''
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labels: enhancement, help wanted, refactors / code health
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assignees: ''
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---
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## Proposed refactoring or deprecation
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<!-- A clear and concise description of the code improvement -->
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### Motivation
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<!-- Please outline the motivation for the proposal. If this is related to another GitHub issue, please link here too -->
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### Pitch
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<!-- A clear and concise description of what you want to happen. -->
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### Additional context
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<!-- Add any other context or screenshots here. -->
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______________________________________________________________________
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#### If you enjoy Lightning, check out our other projects! ⚡
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<sub>
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- [**Metrics**](https://github.com/PyTorchLightning/metrics): Machine learning metrics for distributed, scalable PyTorch applications.
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- [**Flash**](https://github.com/PyTorchLightning/lightning-flash): The fastest way to get a Lightning baseline! A collection of tasks for fast prototyping, baselining, finetuning and solving problems with deep learning
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- [**Bolts**](https://github.com/PyTorchLightning/lightning-bolts): Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch
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- [**Lightning Transformers**](https://github.com/PyTorchLightning/lightning-transformers): Flexible interface for high performance research using SOTA Transformers leveraging Pytorch Lightning, Transformers, and Hydra.
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</sub>

.github/workflows/ci_test-tpu.yml

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.github/workflows/events-recurrent.yml

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steps:
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- name: Setup gcloud CLI
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uses: GoogleCloudPlatform/github-actions/setup-gcloud@master
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uses: google-github-actions/setup-gcloud@master
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with:
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version: '290.0.1'
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service_account_key: ${{ secrets.GKE_SA_KEY_BASE64 }}

.pre-commit-config.yaml

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args: [--py36-plus]
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name: Upgrade code
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- repo: https://github.com/myint/docformatter
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rev: v1.4
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hooks:
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- id: docformatter
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args: [--in-place, --wrap-summaries=115, --wrap-descriptions=120]
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- repo: https://github.com/asottile/yesqa
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rev: v1.2.3
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hooks:

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