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

What do you want to do?

I want to train a custom PyTorch model in Amazon SageMaker.
For a sample Jupyter notebook, see https://github.com/awslabs/amazon-sagemaker-examples/tree/master/sagemaker-python-sdk/pytorch_mnist.
For documentation, see Train a Model with PyTorch.

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

I have a PyTorch model that I trained outside of Amazon SageMaker, and I want to deploy it to an Amazon SageMaker endpoint
Deploy Endpoints from Model Data.

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

I want to see information about Amazon SageMaker PyTorch containers.
https://github.com/aws/sagemaker-pytorch-container.

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

For information about PyTorch versions supported by the Amazon SageMaker PyTorch container, see https://github.com/aws/sagemaker-python-sdk/blob/master/src/sagemaker/pytorch/README.rst.