# PyTorch Distributed

The Kubeflow PyTorch plugin leverages the [Kubeflow training operator](https://github.com/kubeflow/training-operator)
to offer a highly streamlined interface for conducting distributed training using different PyTorch backends.

## Install the plugin

To use the PyTorch plugin, run the following command:

```shell
$ pip install flytekitplugins-kfpytorch
```

To enable the plugin in the backend, follow instructions outlined in the {ref}`deployment-plugin-setup-k8s` guide.

## Run the example on the Flyte cluster

To run the provided examples, use the following commands:

Distributed pytorch training:

```shell
$ pyflyte run --remote pytorch_mnist.py pytorch_training_wf
```

Pytorch lightning training:

```shell
$ pyflyte run --remote pytorch_lightning_mnist_autoencoder.py train_workflow
```

## Subpages

- [Run PyTorch Distributed](https://www.union.ai/docs/v1/flyte/integrations/native-backend-plugins/kfpytorch-plugin/pytorch-mnist/page.md)
- [Use PyTorch Lightning to Train an MNIST Autoencoder](https://www.union.ai/docs/v1/flyte/integrations/native-backend-plugins/kfpytorch-plugin/pytorch-lightning-mnist-autoencoder/page.md)

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**Source**: https://github.com/unionai/unionai-docs/blob/main/content/integrations/native-backend-plugins/kfpytorch-plugin/_index.md
**HTML**: https://www.union.ai/docs/v1/flyte/integrations/native-backend-plugins/kfpytorch-plugin/