Amazon Deep Learning Containers for TensorFlow 2.18 Inference on SageMaker - Amazon Deep Learning Containers
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Amazon Deep Learning Containers for TensorFlow 2.18 Inference on SageMaker

Amazon Deep Learning Containers (DLC) for Amazon SageMaker are now available with support for TensorFlow 2.18 Inference and support for CUDA 12.2 on Ubuntu 20.04. You can launch the new versions of the Deep Learning Containers on the SageMaker service. For a complete list of frameworks and versions supported by the Amazon Deep Learning Containers, see the release notes below.

This release includes container images for inference on CPU and GPU, optimized for performance and scale on Amazon. These Docker images have been tested with SageMaker services, and provide stable versions of NVIDIA CUDA, cuDNN, and other components to provide an optimized user experience for running deep learning workloads on Amazon. All software components in these images are scanned for security vulnerabilities and updated or patched in accordance with Amazon Security best practices. These new DLC are designed to be used on SageMaker inference services.

A list of available containers can be found in our documentation. For latest updates, please also see the aws/deep-learning-containers GitHub repo. Get started quickly with the Amazon 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 forumto get launch announcements and post your questions.

Release Notes

  • Introduced containers of TensorFlow 2.18 for inference on SageMaker.

  • For more details on TensorFlow 2.18 Inference DLCs, please refer to v1.0-tf-sagemaker-2.18.0-inf-py310.

For latest updates, please refer to the aws/deep-learning-containers GitHub repo.

Security Advisory

Python Support

Python 3.10 is supported in the TensorFlow Inference containers.

CPU Instance Type Support

The containers support CPU instance types.

GPU Instance Type support

The containers support GPU instance types and contain the following software components for GPU support:

  • CUDA 12.2

  • cuDNN 8.9.4.25-1+cuda12.2

  • NCCL 2.21.5-1+cuda12.2

Amazon Regions support

The containers are available in the following regions:

Region

Code

US East (Ohio)

us-east-2

US East (N. Virginia)

us-east-1

US West (Oregon)

us-west-2

US West (N. California)

us-west-1

AF South (Cape Town)

af-south-1

Asia Pacific (Hong Kong)

ap-east-1

Asia Pacific (Hyderabad)

ap-south-2

Asia Pacific (Mumbai)

ap-south-1

Asia Pacific (Osaka)

ap-northeast-3

Asia Pacific (Seoul)

ap-northeast-2

Asia Pacific (Tokyo)

ap-northeast-1

Asia Pacific (Melbourne)

ap-southeast-4

Asia Pacific (Jakarta)

ap-southeast-3

Asia Pacific (Sydney)

ap-southeast-2

Asia Pacific (Singapore)

ap-southeast-1

Asia Pacific (Malaysia)

ap-southeast-5

Central (Canada)

ca-central-1

Canada (Calgary)

ca-west-1

EU (Zurich)

eu-central-2

EU (Frankfurt)

eu-central-1

EU (Ireland)

eu-west-1

EU (London)

eu-west-2

EU( Paris)

eu-west-3

EU (Spain)

eu-south-2

EU (Milan)

eu-south-1

EU (Stockholm)

eu-north-1

Israel (Tel Aviv)

il-central-1

Middle East (Bahrain)

me-south-1

Middle East (UAE)

me-central-1

SA (Sau Paulo)

sa-east-1

China (Beijing)

cn-north-1

China (Ningxia)

cn-northwest-1

Build and Test

  • Built on: c5.18xlarge

  • Tested on: c4.8xlarge, c5.18xlarge, m4.16xlarge, p3.16xlarge, p3dn.24xlarge, p4d.24xlarge, g4dn.xlarge