AWS Deep Learning Containers for PyTorch 1.5.0
The AWS Deep Learning Containers are available today with the latest framework versions of PyTorch 1.5.0, with newly added SageMaker Inference, SageMaker PyTorch Inference, and the latest version of SageMaker PyTorch Training. You can launch the new versions of the Deep Learning Containers on Amazon SageMaker, Amazon Elastic Kubernetes Service (Amazon EKS), self-managed Kubernetes on Amazon EC2, and Amazon Elastic Container Service (Amazon ECS). For a complete list of frameworks and versions supported by the AWS Deep Learning Containers, see the release notes for PyTorch 1.5.0.
The AWS Deep Learning Containers for PyTorch include containers for training on CPU and GPU, optimized for performance and scale on AWS. These Docker images have been tested with Amazon SageMaker, EC2, ECS, and EKS, and provide stable versions of NVIDIA CUDA, cuDNN, Intel MKL, and other required software components to provide a seamless user experience for deep learning workloads. All software components in these images are scanned for security vulnerabilities and updated or patched in accordance with AWS Security best practices.
More details can be found in the 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.