Use PyTorch with Amazon SageMaker

You can use Amazon SageMaker to train and deploy a model using custom PyTorch code. The SageMaker Python SDK PyTorch estimators and models and the SageMaker open-source PyTorch container make writing a PyTorch script and running it in SageMaker easier.

What do you want to do?

I want to train a custom PyTorch model in SageMaker.

For a sample Jupyter notebook, see the PyTorch example notebook in the Amazon SageMaker Examples GitHub repository.

For documentation, see Train a Model with PyTorch.

I have a PyTorch model that I trained in SageMaker, and I want to deploy it to a hosted endpoint.

For more information, see Deploy PyTorch models.

I have a PyTorch model that I trained outside of SageMaker, and I want to deploy it to a SageMaker endpoint

For more information, see Deploy Endpoints from Model Data.

I want to see the API documentation for Amazon SageMaker Python SDK PyTorch classes.

For more information, see PyTorch Classes.

I want to find the SageMaker PyTorch container repository.

For more information, see SageMaker PyTorch Container GitHub repository.

I want to find information about PyTorch versions supported by AWS Deep Learning Containers.

For more information, see Available Deep Learning Container Images.

For general information about writing PyTorch training scripts and using PyTorch estimators and models with SageMaker, see Using PyTorch with the SageMaker Python SDK.