AWS Deep Learning Containers now support PyTorch
AWS Deep Learning (DL) Containers now support PyTorch. AWS DL Containers are Docker images pre-installed with deep learning frameworks to make it easy to setup and deploy custom machine learning environments. Docker images for training and inference with PyTorch are now available through Amazon Elastic Container Registry (Amazon ECR) free of charge—you pay only for the resources that you use. You can deploy AWS DL Containers on Amazon SageMaker, Amazon Elastic Kubernetes Service (Amazon EKS), self-managed Kubernetes on Amazon EC2, and Amazon Elastic Container Service (Amazon ECS).
AWS Deep Learning (DL) Containers now support PyTorch. AWS DL Containers are Docker images pre-installed with deep learning frameworks to make it easy to setup and deploy custom machine learning environments. Docker images for training and inference with PyTorch are now available through Amazon Elastic Container Registry (Amazon ECR) free of charge—you pay only for the resources that you use. You can deploy AWS DL Containers on Amazon SageMaker, Amazon Elastic Kubernetes Service (Amazon EKS), self-managed Kubernetes on Amazon EC2, and Amazon Elastic Container Service (Amazon ECS).
AWS DL Containers are continually updated with the latest deep learning libraries and optimized for CPU and GPU resources on AWS. For more information, see AWS Deep Learning Containers. You can get started with AWS DL Containers for PyTorch here and review release notes and the bill of materials for Docker images here.