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.
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For more information, see SageMaker PyTorch Container GitHub repository
. - I want to find information about PyTorch versions supported by AWS Deep Learning Containers.
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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