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______________________________________________________________________ ______________________________________________________________________
<p align="center"> <p align="center">
<a href="https://lightning.ai/">Lightning.ai</a> • <a href="https://lightning.ai/">Lightning AI</a> •
<a href="#examples">Examples</a> •
<a href="https://lightning.ai/docs/pytorch/stable/">PyTorch Lightning</a> • <a href="https://lightning.ai/docs/pytorch/stable/">PyTorch Lightning</a> •
<a href="https://lightning.ai/docs/fabric/stable/">Fabric</a> • <a href="https://lightning.ai/docs/fabric/stable/">Fabric</a> •
<a href="https://lightning.ai/docs/app/stable/">Lightning Apps</a> •
<a href="https://pytorch-lightning.readthedocs.io/en/stable/">Docs</a> • <a href="https://pytorch-lightning.readthedocs.io/en/stable/">Docs</a> •
<a href="#community">Community</a> • <a href="#community">Community</a> •
<a href="https://lightning.ai/docs/pytorch/stable/generated/CONTRIBUTING.html">Contribute</a> • <a href="https://lightning.ai/docs/pytorch/stable/generated/CONTRIBUTING.html">Contribute</a> •
@ -92,15 +92,11 @@ pip install -iU https://test.pypi.org/simple/ pytorch-lightning
______________________________________________________________________ ______________________________________________________________________
## Lightning has 4 core packages ## Lightning has 2 core packages
[PyTorch Lightning: Train and deploy PyTorch at scale](#pytorch-lightning-train-and-deploy-pytorch-at-scale). [PyTorch Lightning: Train and deploy PyTorch at scale](#pytorch-lightning-train-and-deploy-pytorch-at-scale).
<br/> <br/>
[Lightning Fabric: Expert control](#lightning-fabric-expert-control). [Lightning Fabric: Expert control](#lightning-fabric-expert-control).
<br/>
[Lightning Data: Blazing fast, distributed streaming of training data from cloud storage](https://github.com/Lightning-AI/pytorch-lightning/tree/master/src/lightning/data).
<br/>
[Lightning Apps: Build AI products and ML workflows](#lightning-apps-build-ai-products-and-ml-workflows).
Lightning gives you granular control over how much abstraction you want to add over PyTorch. Lightning gives you granular control over how much abstraction you want to add over PyTorch.
@ -108,7 +104,9 @@ Lightning gives you granular control over how much abstraction you want to add o
<img src="https://pl-public-data.s3.amazonaws.com/assets_lightning/continuum.png" width="80%"> <img src="https://pl-public-data.s3.amazonaws.com/assets_lightning/continuum.png" width="80%">
</div> </div>
______________________________________________________________________ &nbsp;
&nbsp;
# PyTorch Lightning: Train and Deploy PyTorch at Scale # PyTorch Lightning: Train and Deploy PyTorch at Scale
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______________________________________________________________________ ______________________________________________________________________
### Examples
Explore various types of training possible with PyTorch Lightning. Pretrain and finetune ANY kind of model to perform ANY task like classification, segmentation, summarization and more:
| Task | Description | Run |
|---|---|---|
| [Hello world](#hello-simple-model) | Pretrain - Hello world example | <a target="_blank" href="https://lightning.ai/lightning-ai/studios/pytorch-lightning-hello-world"><img src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/app-2/studio-badge.svg" alt="Open In Studio"/></a> |
| [Image segmentation](https://lightning.ai/lightning-ai/studios/image-segmentation-with-pytorch-lightning) | Finetune - ResNet-50 model to segment images | <a target="_blank" href="https://lightning.ai/lightning-ai/studios/image-segmentation-with-pytorch-lightning"><img src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/app-2/studio-badge.svg" alt="Open In Studio"/></a> |
| [Text classification](https://lightning.ai/lightning-ai/studios/text-classification-with-pytorch-lightning) | Finetune - text classifier (BERT model) | <a target="_blank" href="https://lightning.ai/lightning-ai/studios/text-classification-with-pytorch-lightning"><img src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/app-2/studio-badge.svg" alt="Open In Studio"/></a> |
### Hello simple model ### Hello simple model
```python ```python
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______________________________________________________________________ ______________________________________________________________________
&nbsp;
&nbsp;
# Lightning Fabric: Expert control. # Lightning Fabric: Expert control.
Run on any device at any scale with expert-level control over PyTorch training loop and scaling strategy. You can even write your own Trainer. Run on any device at any scale with expert-level control over PyTorch training loop and scaling strategy. You can even write your own Trainer.
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______________________________________________________________________ ______________________________________________________________________
# Lightning Apps: Build AI products and ML workflows &nbsp;
&nbsp;
Lightning Apps remove the cloud infrastructure boilerplate so you can focus on solving the research or business problems. Lightning Apps can run on the Lightning Cloud, your own cluster or a private cloud.
<div align="center">
<img src="https://pl-public-data.s3.amazonaws.com/assets_lightning/lightning-apps-teaser.png" width="80%">
</div>
## Hello Lightning app world
```python
# app.py
import lightning as L
class TrainComponent(L.LightningWork):
def run(self, x):
print(f"train a model on {x}")
class AnalyzeComponent(L.LightningWork):
def run(self, x):
print(f"analyze model on {x}")
class WorkflowOrchestrator(L.LightningFlow):
def __init__(self) -> None:
super().__init__()
self.train = TrainComponent(cloud_compute=L.CloudCompute("cpu"))
self.analyze = AnalyzeComponent(cloud_compute=L.CloudCompute("gpu"))
def run(self):
self.train.run("CPU machine 1")
self.analyze.run("GPU machine 2")
app = L.LightningApp(WorkflowOrchestrator())
```
Run on the cloud or locally
```bash
# run on the cloud
lightning run app app.py --setup --cloud
# run locally
lightning run app app.py
```
______________________________________________________________________
<div align="center">
<a href="https://lightning.ai/docs/app/stable/">Read the Lightning Apps docs</a>
</div>
______________________________________________________________________
## Examples ## Examples
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- [Logistic Regression](https://lightning-bolts.readthedocs.io/en/stable/models/classic_ml.html#logistic-regression) - [Logistic Regression](https://lightning-bolts.readthedocs.io/en/stable/models/classic_ml.html#logistic-regression)
- [Linear Regression](https://lightning-bolts.readthedocs.io/en/stable/models/classic_ml.html#linear-regression) - [Linear Regression](https://lightning-bolts.readthedocs.io/en/stable/models/classic_ml.html#linear-regression)
______________________________________________________________________ &nbsp;
&nbsp;
## Continuous Integration ## Continuous Integration
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</center> </center>
</details> </details>
______________________________________________________________________ &nbsp;
&nbsp;
## Community ## Community