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Resources for using Apache MXNet with Amazon SageMaker AI - Amazon SageMaker AI
What do you want to do?

Resources for using Apache MXNet with Amazon SageMaker AI

Important

Deprecation notice: Apache MXNet is not supported in SageMaker Python SDK v3. If you are currently using MXNet, continue using SageMaker Python SDK v2. For new projects, consider using PyTorch or TensorFlow with the unified ModelTrainer class. See SageMaker Python SDK documentation for migration guidance.

The Amazon SageMaker Python SDK MXNet estimators and models and the SageMaker AI open-source MXNet container make writing a MXNet script and running it in SageMaker AI easier. The following section provides reference material you can use to learn how to use SageMaker AI to train and deploy a model using custom MXNet code.

What do you want to do?

I want to train a custom MXNet model in SageMaker AI.

For documentation, see Train a Model with MXNet.

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

For more information, see Deploy MXNet models.

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

For more information, see Deploy Endpoints from Model Data.

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

For more information, see MXNet Classes.

I want to find the SageMaker AI MXNet container repository.

For more information, see SageMaker AI MXNet Container GitHub repository.

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

For more information, see Available Deep Learning Container Images.

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