AWS Deep Learning Containers (AWS DL Containers) give machine learning and deep learning practitioners optimized Docker environments to train and deploy models in their pipelines and workflows across Amazon Sagemaker, Amazon EC2, Amazon ECS, and Amazon EKS. AWS DL Containers are available as Docker images for training and inference with TensorFlow, PyTorch, and MXNet on Amazon ECR.
AWS DL Containers are kept current with the latest versions of frameworks and drivers, are tested for compatibility and security, and are offered at no additional cost. They are also customizable by following our recipe guides. Using AWS DL Containers as a building block for ML environments reduces the burden on operations and infrastructure teams, lowers the operating cost, accelerates the development of ML products, and enables the ML teams to focus on the value added work of deriving ML-powered insights from the organization’s data. DL Containers are kept current with the latest versions of frameworks and drivers, are tested for compatibility and security, and are offered at no additional cost. They are also customizable by following our recipe guides. Using DL Containers as a building block for ML environments reduces the burden on operations and infrastructure teams, lowers the operating cost, accelerates the development of ML products, and enables the ML teams to focus on the value added work of deriving ML-powered insights from the organization’s data.
AWS DL Containers are built, tested, and optimized to be used in Amazon Sagemaker, Amazon EC2, Amazon ECS, and Amazon EKS. Docker images for AWS DL Containers are available on Amazon ECR. For training and inference of deep learning models using GPUs, AWS DL Containers require the underlying Amazon Machine Image (AMI) to have the appropriate GPU drivers installed. DL Containers are built to work with the default GPU AMIs available in Amazon SageMaker, Amazon ECS, and Amazon EKS.
AWS Deep Learning AMIs are EC2 Amazon Machine Images (AMIs) built and optimized for building, training, and inference of machine learning and deep learning models. For more information, see AWS Deep Learning AMIs. For more information about using AWS DL Containers in EC2, see the documentation.
AWS DL Containers are available at no additional charge. You pay only for the Amazon Sagemaker, Amazon EC2, Amazon ECS, Amazon EKS, and other AWS resources that you use.
You can access Docker images for AWS DL Containers from repositories in Amazon ECR. For more information, see the documentation for a list of available Docker images.