SageMaker MXNet Training Toolkit is an open-source library for using MXNet to train models on Amazon SageMaker. For inference, see SageMaker MXNet Inference Toolkit. For the Dockerfiles used for building SageMaker MXNet Containers, see AWS Deep Learning Containers. For information on running MXNet jobs on Amazon SageMaker, please refer to the SageMaker Python SDK documentation. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. If you have your own algorithms built into SageMaker compatible Docker containers, you can train and host models using these as well.
Features
- Set up a virtual environment for testing
- To run integration tests locally, one needs to build an image. To trigger image build, use -B flag.
- Make sure to provide AWS account ID, Region, Docker base name & Tag
- SageMaker MXNet Training Toolkit is licensed under the Apache 2.0 License
- run all tests within a folder [e.g. integration/local/]
- Setup a virtual environment