Amazon SageMaker
Developer Guide

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Use Chainer with Amazon SageMaker

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

What do you want to do?

I want to train a custom Chainer model in Amazon SageMaker.

For a sample Jupyter notebook, see https://github.com/awslabs/amazon-sagemaker-examples/tree/master/sagemaker-python-sdk/chainer_mnist.

For documentation, see Train a Model with Chainer.

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

Deploy Chainer models.

I have a Chainer 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 Chainer classes.

Chainer Classes

I want to see information about Amazon SageMaker Chainer containers.

https://github.com/aws/sagemaker-chainer-container.

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

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

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