Posted On: Mar 24, 2020
The AWS Deep Learning Containers are available today with the latest framework versions of TensorFlow 2.1.0 & 1.15.2, PyTorch 1.4.0, and MXNet 1.6.0 . The release includes the addition of HAQM SageMaker Python SDK in the containers, and updates to the HAQM SageMaker Experiments package. HAQM SageMaker Experiments is a feature in HAQM SageMaker that lets you organize, track, compare, and evaluate machine learning (ML) experiments and model versions. The TensorFlow 2.1.0 python3 training containers now also include SageMaker Debugger, which allow data scientists to save and inspect the model tensors during training jobs.
You can launch the new versions of the Deep Learning Containers on HAQM SageMaker, HAQM Elastic Kubernetes Service (HAQM EKS), self-managed Kubernetes on HAQM EC2, and HAQM Elastic Container Service (HAQM ECS). For a complete list of frameworks, end-of-life announcements, and versions supported by the AWS Deep Learning Containers, see release notes for PyTorch 1.4.0, MXNet 1.6.0, TensorFlow 2.1.0, and TensorFlow 1.15.2.
More details can be found in the AWS marketplace, and a list of available containers can be found in our documentation. Get started quickly with the AWS Deep Learning Containers using the getting-started guides and beginner to advanced level tutorials in our developer guide. You can also subscribe to our discussion forum to get launch announcements and post your questions.