---
tags: [basic, vision]
dataset: [CIFAR-10]
framework: [torch]
---

# app-pytorch: A Flower / PyTorch app

[<img src="_static/view-gh.png" alt="View on GitHub" width="200"/>](https://github.com/adap/flower/blob/main/examples/app-pytorch)

> [!NOTE]
> This example is a playground for upcoming features with Flower's `Message API`.

## Install dependencies and project

```bash
pip install -e .
```

## Run with the Simulation Engine

In the `app-pytorch` directory, use `flwr run` to run a local simulation:

```bash
flwr run .
```

Refer to the [How to Run Simulations](https://flower.ai/docs/framework/how-to-run-simulations.html) guide in the documentation for advice on how to optimize your simulations.

## Run with the Deployment Engine

Follow this [how-to guide](https://flower.ai/docs/framework/how-to-run-flower-with-deployment-engine.html) to run the same app in this example but with Flower's Deployment Engine. After that, you might be intersted in setting up [secure TLS-enabled communications](https://flower.ai/docs/framework/how-to-enable-tls-connections.html) and [SuperNode authentication](https://flower.ai/docs/framework/how-to-authenticate-supernodes.html) in your federation.

If you are already familiar with how the Deployment Engine works, you may want to learn how to run it using Docker. Check out the [Flower with Docker](https://flower.ai/docs/framework/docker/index.html) documentation.

## Resources

- Flower website: [flower.ai](https://flower.ai/)
- Check the documentation: [flower.ai/docs](https://flower.ai/docs/)
- Give Flower a ⭐️ on GitHub: [GitHub](https://github.com/adap/flower)
- Join the Flower community!
  - [Flower Slack](https://flower.ai/join-slack/)
  - [Flower Discuss](https://discuss.flower.ai/)