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@@ -0,0 +1 @@ +/lightning-bolts-0.6.0.post1.tar.gz diff --git a/python-lightning-bolts.spec b/python-lightning-bolts.spec new file mode 100644 index 0000000..ca8b17d --- /dev/null +++ b/python-lightning-bolts.spec @@ -0,0 +1,526 @@ +%global _empty_manifest_terminate_build 0 +Name: python-lightning-bolts +Version: 0.6.0.post1 +Release: 1 +Summary: Lightning Bolts is a community contribution for ML researchers. +License: Apache-2.0 +URL: https://github.com/Lightning-AI/lightning-bolts +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/f0/23/0e5e5b5cfc2202f56b48353dc52dc91d3c4b85b09cb6439d996481491d45/lightning-bolts-0.6.0.post1.tar.gz +BuildArch: noarch + +Requires: python3-pytorch-lightning +Requires: python3-lightning-utilities +Requires: python3-torchvision +Requires: python3-torchvision +Requires: python3-scikit-learn +Requires: python3-Pillow +Requires: python3-opencv-python-headless +Requires: python3-gym[atari] +Requires: python3-atari-py +Requires: python3-box2d-py +Requires: python3-opencv-python +Requires: python3-matplotlib +Requires: python3-wandb +Requires: python3-scipy +Requires: python3-codecov +Requires: python3-pytest +Requires: python3-pytest-cov +Requires: python3-check-manifest +Requires: python3-pre-commit +Requires: python3-mypy +Requires: python3-atari-py +Requires: python3-scikit-learn +Requires: python3-sparseml +Requires: python3-ale-py +Requires: python3-jsonargparse[signatures] +Requires: python3-torchvision +Requires: python3-scikit-learn +Requires: python3-Pillow +Requires: python3-opencv-python-headless +Requires: python3-gym[atari] +Requires: python3-atari-py +Requires: python3-box2d-py +Requires: python3-opencv-python +Requires: python3-matplotlib +Requires: python3-wandb +Requires: python3-scipy +Requires: python3-matplotlib +Requires: python3-wandb +Requires: python3-scipy +Requires: python3-torchvision +Requires: python3-scikit-learn +Requires: python3-Pillow +Requires: python3-opencv-python-headless +Requires: python3-gym[atari] +Requires: python3-atari-py +Requires: python3-box2d-py +Requires: python3-opencv-python +Requires: python3-codecov +Requires: python3-pytest +Requires: python3-pytest-cov +Requires: python3-check-manifest +Requires: python3-pre-commit +Requires: python3-mypy +Requires: python3-atari-py +Requires: python3-scikit-learn +Requires: python3-sparseml +Requires: python3-ale-py +Requires: python3-jsonargparse[signatures] + +%description +<div align="center"> + +<img src="https://github.com/Lightning-AI/lightning-bolts/raw/0.6.0.post1/docs/source/_images/logos/bolts_logo.png" width="400px"> + +**Deep Learning components for extending PyTorch Lightning** + +______________________________________________________________________ + +<p align="center"> + <a href="#install">Installation</a> • + <a href="https://lightning-bolts.readthedocs.io/en/latest/">Latest Docs</a> • + <a href="https://lightning-bolts.readthedocs.io/en/0.6.0.post1">Stable Docs</a> • + <a href="#what-is-bolts">About</a> • + <a href="#team">Community</a> • + <a href="https://www.pytorchlightning.ai/">Website</a> • + <a href="https://www.grid.ai/">Grid AI</a> • + <a href="#license">License</a> +</p> + +[](https://badge.fury.io/py/lightning-bolts) +[](https://pepy.tech/project/lightning-bolts) +[](https://dev.azure.com/Lightning-AI/lightning%20Bolts/_build?definitionId=31&_a=summary&repositoryFilter=13&branchFilter=4923%2C4923) +[](https://codecov.io/gh/Lightning-AI/lightning-bolts) + +[](https://lightning-bolts.readthedocs.io/en/latest/) +[](https://www.pytorchlightning.ai/community) +[](https://github.com/PytorchLightning/lightning-bolts/blob/master/LICENSE) + +</div> + +______________________________________________________________________ + +## Getting Started + +Pip / Conda + +```bash +pip install lightning-bolts +``` + +<details> + <summary>Other installations</summary> + +Install bleeding-edge (no guarantees) + +```bash +pip install git+https://github.com/PytorchLightning/lightning-bolts.git@master --upgrade +``` + +To install all optional dependencies + +```bash +pip install lightning-bolts["extra"] +``` + +</details> + +## What is Bolts + +Bolts provides a variety of components to extend PyTorch Lightning such as callbacks & datasets, for applied research and production. + +## News + +- Sept 22: [Leverage Sparsity for Faster Inference with Lightning Flash and SparseML](https://devblog.pytorchlightning.ai/leverage-sparsity-for-faster-inference-with-lightning-flash-and-sparseml-cdda1165622b) +- Aug 26: [Fine-tune Transformers Faster with Lightning Flash and Torch ORT](https://devblog.pytorchlightning.ai/fine-tune-transformers-faster-with-lightning-flash-and-torch-ort-ec2d53789dc3) + +#### Example 1: Accelerate Lightning Training with the Torch ORT Callback + +Torch ORT converts your model into an optimized ONNX graph, speeding up training & inference when using NVIDIA or AMD GPUs. See the [documentation](https://lightning-bolts.readthedocs.io/en/latest/callbacks/torch_ort.html) for more details. + +```python +from pytorch_lightning import LightningModule, Trainer +import torchvision.models as models +from pl_bolts.callbacks import ORTCallback + + +class VisionModel(LightningModule): + def __init__(self): + super().__init__() + self.model = models.vgg19_bn(pretrained=True) + + ... + + +model = VisionModel() +trainer = Trainer(gpus=1, callbacks=ORTCallback()) +trainer.fit(model) +``` + +#### Example 2: Introduce Sparsity with the SparseMLCallback to Accelerate Inference + +We can introduce sparsity during fine-tuning with [SparseML](https://github.com/neuralmagic/sparseml), which ultimately allows us to leverage the [DeepSparse](https://github.com/neuralmagic/deepsparse) engine to see performance improvements at inference time. + +```python +from pytorch_lightning import LightningModule, Trainer +import torchvision.models as models +from pl_bolts.callbacks import SparseMLCallback + + +class VisionModel(LightningModule): + def __init__(self): + super().__init__() + self.model = models.vgg19_bn(pretrained=True) + + ... + + +model = VisionModel() +trainer = Trainer(gpus=1, callbacks=SparseMLCallback(recipe_path="recipe.yaml")) +trainer.fit(model) +``` + +## Are specific research implementations supported? + +We'd like to encourage users to contribute general components that will help a broad range of problems, however components that help specifics domains will also be welcomed! + +For example a callback to help train SSL models would be a great contribution, however the next greatest SSL model from your latest paper would be a good contribution to [Lightning Flash](https://github.com/PyTorchLightning/lightning-flash). + +Use [Lightning Flash](https://github.com/PyTorchLightning/lightning-flash) to train, predict and serve state-of-the-art models for applied research. We suggest looking at our [VISSL](https://lightning-flash.readthedocs.io/en/latest/integrations/vissl.html) Flash integration for SSL based tasks. + +## Contribute! + +Bolts is supported by the PyTorch Lightning team and the PyTorch Lightning community! + +Join our Slack and/or read our [CONTRIBUTING](./.github/CONTRIBUTING.md) guidelines to get help becoming a contributor! + +______________________________________________________________________ + +## License + +Please observe the Apache 2.0 license that is listed in this repository. +In addition the Lightning framework is Patent Pending. + + +%package -n python3-lightning-bolts +Summary: Lightning Bolts is a community contribution for ML researchers. +Provides: python-lightning-bolts +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-lightning-bolts +<div align="center"> + +<img src="https://github.com/Lightning-AI/lightning-bolts/raw/0.6.0.post1/docs/source/_images/logos/bolts_logo.png" width="400px"> + +**Deep Learning components for extending PyTorch Lightning** + +______________________________________________________________________ + +<p align="center"> + <a href="#install">Installation</a> • + <a href="https://lightning-bolts.readthedocs.io/en/latest/">Latest Docs</a> • + <a href="https://lightning-bolts.readthedocs.io/en/0.6.0.post1">Stable Docs</a> • + <a href="#what-is-bolts">About</a> • + <a href="#team">Community</a> • + <a href="https://www.pytorchlightning.ai/">Website</a> • + <a href="https://www.grid.ai/">Grid AI</a> • + <a href="#license">License</a> +</p> + +[](https://badge.fury.io/py/lightning-bolts) +[](https://pepy.tech/project/lightning-bolts) +[](https://dev.azure.com/Lightning-AI/lightning%20Bolts/_build?definitionId=31&_a=summary&repositoryFilter=13&branchFilter=4923%2C4923) +[](https://codecov.io/gh/Lightning-AI/lightning-bolts) + +[](https://lightning-bolts.readthedocs.io/en/latest/) +[](https://www.pytorchlightning.ai/community) +[](https://github.com/PytorchLightning/lightning-bolts/blob/master/LICENSE) + +</div> + +______________________________________________________________________ + +## Getting Started + +Pip / Conda + +```bash +pip install lightning-bolts +``` + +<details> + <summary>Other installations</summary> + +Install bleeding-edge (no guarantees) + +```bash +pip install git+https://github.com/PytorchLightning/lightning-bolts.git@master --upgrade +``` + +To install all optional dependencies + +```bash +pip install lightning-bolts["extra"] +``` + +</details> + +## What is Bolts + +Bolts provides a variety of components to extend PyTorch Lightning such as callbacks & datasets, for applied research and production. + +## News + +- Sept 22: [Leverage Sparsity for Faster Inference with Lightning Flash and SparseML](https://devblog.pytorchlightning.ai/leverage-sparsity-for-faster-inference-with-lightning-flash-and-sparseml-cdda1165622b) +- Aug 26: [Fine-tune Transformers Faster with Lightning Flash and Torch ORT](https://devblog.pytorchlightning.ai/fine-tune-transformers-faster-with-lightning-flash-and-torch-ort-ec2d53789dc3) + +#### Example 1: Accelerate Lightning Training with the Torch ORT Callback + +Torch ORT converts your model into an optimized ONNX graph, speeding up training & inference when using NVIDIA or AMD GPUs. See the [documentation](https://lightning-bolts.readthedocs.io/en/latest/callbacks/torch_ort.html) for more details. + +```python +from pytorch_lightning import LightningModule, Trainer +import torchvision.models as models +from pl_bolts.callbacks import ORTCallback + + +class VisionModel(LightningModule): + def __init__(self): + super().__init__() + self.model = models.vgg19_bn(pretrained=True) + + ... + + +model = VisionModel() +trainer = Trainer(gpus=1, callbacks=ORTCallback()) +trainer.fit(model) +``` + +#### Example 2: Introduce Sparsity with the SparseMLCallback to Accelerate Inference + +We can introduce sparsity during fine-tuning with [SparseML](https://github.com/neuralmagic/sparseml), which ultimately allows us to leverage the [DeepSparse](https://github.com/neuralmagic/deepsparse) engine to see performance improvements at inference time. + +```python +from pytorch_lightning import LightningModule, Trainer +import torchvision.models as models +from pl_bolts.callbacks import SparseMLCallback + + +class VisionModel(LightningModule): + def __init__(self): + super().__init__() + self.model = models.vgg19_bn(pretrained=True) + + ... + + +model = VisionModel() +trainer = Trainer(gpus=1, callbacks=SparseMLCallback(recipe_path="recipe.yaml")) +trainer.fit(model) +``` + +## Are specific research implementations supported? + +We'd like to encourage users to contribute general components that will help a broad range of problems, however components that help specifics domains will also be welcomed! + +For example a callback to help train SSL models would be a great contribution, however the next greatest SSL model from your latest paper would be a good contribution to [Lightning Flash](https://github.com/PyTorchLightning/lightning-flash). + +Use [Lightning Flash](https://github.com/PyTorchLightning/lightning-flash) to train, predict and serve state-of-the-art models for applied research. We suggest looking at our [VISSL](https://lightning-flash.readthedocs.io/en/latest/integrations/vissl.html) Flash integration for SSL based tasks. + +## Contribute! + +Bolts is supported by the PyTorch Lightning team and the PyTorch Lightning community! + +Join our Slack and/or read our [CONTRIBUTING](./.github/CONTRIBUTING.md) guidelines to get help becoming a contributor! + +______________________________________________________________________ + +## License + +Please observe the Apache 2.0 license that is listed in this repository. +In addition the Lightning framework is Patent Pending. + + +%package help +Summary: Development documents and examples for lightning-bolts +Provides: python3-lightning-bolts-doc +%description help +<div align="center"> + +<img src="https://github.com/Lightning-AI/lightning-bolts/raw/0.6.0.post1/docs/source/_images/logos/bolts_logo.png" width="400px"> + +**Deep Learning components for extending PyTorch Lightning** + +______________________________________________________________________ + +<p align="center"> + <a href="#install">Installation</a> • + <a href="https://lightning-bolts.readthedocs.io/en/latest/">Latest Docs</a> • + <a href="https://lightning-bolts.readthedocs.io/en/0.6.0.post1">Stable Docs</a> • + <a href="#what-is-bolts">About</a> • + <a href="#team">Community</a> • + <a href="https://www.pytorchlightning.ai/">Website</a> • + <a href="https://www.grid.ai/">Grid AI</a> • + <a href="#license">License</a> +</p> + +[](https://badge.fury.io/py/lightning-bolts) +[](https://pepy.tech/project/lightning-bolts) +[](https://dev.azure.com/Lightning-AI/lightning%20Bolts/_build?definitionId=31&_a=summary&repositoryFilter=13&branchFilter=4923%2C4923) +[](https://codecov.io/gh/Lightning-AI/lightning-bolts) + +[](https://lightning-bolts.readthedocs.io/en/latest/) +[](https://www.pytorchlightning.ai/community) +[](https://github.com/PytorchLightning/lightning-bolts/blob/master/LICENSE) + +</div> + +______________________________________________________________________ + +## Getting Started + +Pip / Conda + +```bash +pip install lightning-bolts +``` + +<details> + <summary>Other installations</summary> + +Install bleeding-edge (no guarantees) + +```bash +pip install git+https://github.com/PytorchLightning/lightning-bolts.git@master --upgrade +``` + +To install all optional dependencies + +```bash +pip install lightning-bolts["extra"] +``` + +</details> + +## What is Bolts + +Bolts provides a variety of components to extend PyTorch Lightning such as callbacks & datasets, for applied research and production. + +## News + +- Sept 22: [Leverage Sparsity for Faster Inference with Lightning Flash and SparseML](https://devblog.pytorchlightning.ai/leverage-sparsity-for-faster-inference-with-lightning-flash-and-sparseml-cdda1165622b) +- Aug 26: [Fine-tune Transformers Faster with Lightning Flash and Torch ORT](https://devblog.pytorchlightning.ai/fine-tune-transformers-faster-with-lightning-flash-and-torch-ort-ec2d53789dc3) + +#### Example 1: Accelerate Lightning Training with the Torch ORT Callback + +Torch ORT converts your model into an optimized ONNX graph, speeding up training & inference when using NVIDIA or AMD GPUs. See the [documentation](https://lightning-bolts.readthedocs.io/en/latest/callbacks/torch_ort.html) for more details. + +```python +from pytorch_lightning import LightningModule, Trainer +import torchvision.models as models +from pl_bolts.callbacks import ORTCallback + + +class VisionModel(LightningModule): + def __init__(self): + super().__init__() + self.model = models.vgg19_bn(pretrained=True) + + ... + + +model = VisionModel() +trainer = Trainer(gpus=1, callbacks=ORTCallback()) +trainer.fit(model) +``` + +#### Example 2: Introduce Sparsity with the SparseMLCallback to Accelerate Inference + +We can introduce sparsity during fine-tuning with [SparseML](https://github.com/neuralmagic/sparseml), which ultimately allows us to leverage the [DeepSparse](https://github.com/neuralmagic/deepsparse) engine to see performance improvements at inference time. + +```python +from pytorch_lightning import LightningModule, Trainer +import torchvision.models as models +from pl_bolts.callbacks import SparseMLCallback + + +class VisionModel(LightningModule): + def __init__(self): + super().__init__() + self.model = models.vgg19_bn(pretrained=True) + + ... + + +model = VisionModel() +trainer = Trainer(gpus=1, callbacks=SparseMLCallback(recipe_path="recipe.yaml")) +trainer.fit(model) +``` + +## Are specific research implementations supported? + +We'd like to encourage users to contribute general components that will help a broad range of problems, however components that help specifics domains will also be welcomed! + +For example a callback to help train SSL models would be a great contribution, however the next greatest SSL model from your latest paper would be a good contribution to [Lightning Flash](https://github.com/PyTorchLightning/lightning-flash). + +Use [Lightning Flash](https://github.com/PyTorchLightning/lightning-flash) to train, predict and serve state-of-the-art models for applied research. We suggest looking at our [VISSL](https://lightning-flash.readthedocs.io/en/latest/integrations/vissl.html) Flash integration for SSL based tasks. + +## Contribute! + +Bolts is supported by the PyTorch Lightning team and the PyTorch Lightning community! + +Join our Slack and/or read our [CONTRIBUTING](./.github/CONTRIBUTING.md) guidelines to get help becoming a contributor! + +______________________________________________________________________ + +## License + +Please observe the Apache 2.0 license that is listed in this repository. +In addition the Lightning framework is Patent Pending. + + +%prep +%autosetup -n lightning-bolts-0.6.0.post1 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-lightning-bolts -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.0.post1-1 +- Package Spec generated @@ -0,0 +1 @@ +b212e718c27c63567f2bb0ee644b5f1d lightning-bolts-0.6.0.post1.tar.gz |