Deep Learning AMI
Developer Guide

Document History for AWS Deep Learning AMI Developer Guide

Change Description Date

Installing PyTorch from a Nightly Build

A tutorial was added that covers how you can uninstall PyTorch, then install a nightly build of PyTorch on your Deep Learning AMI with Conda.

September 25, 2018

Docker is now pre-installed on your DLAMI

Since v14 of the Deep Learning AMI with Conda, Docker and NVIDIA's version of Docker for GPUs has been pre-installed.

September 25, 2018

TensorBoard Tutorial

Example was moved to ~/examples/tensorboard. Tutorial paths updated.

July 23, 2018

MXBoard Tutorial

A tutorial on how to use MXBoard for visualization of MXNet models was addded.

July 23, 2018

Distributed Training Tutorials

A tutorial on how to use Keras-MXNet for multi-GPU training was added. Chainer's tutorial was updated to for v4.2.0.

July 23, 2018

Conda Tutorial

The example MOTD was updated to reflect a more recent release.

July 23, 2018

Chainer Tutorial

The tutorial was updated to use the latest examples from Chainer's source.

July 23, 2018

Earlier Updates:

The following table describes important changes in each release of the AWS Deep Learning AMI before July, 2018.

Change Description Date
TensorFlow with Horovod Added a tutorial for training ImageNet with TensorFlow and Horovod. June 6, 2018
Upgrading guide Added the upgrading guide. May 15, 2018
New regions and new 10 minute tutorial New regions added: US West (N. California), South America, Canada (Central), EU (London), and EU (Paris). Also, the first release of a 10-minute tutorial titled: "Getting Started with Deep Learning AMI". April 26, 2018
Chainer tutorial A tutorial for using Chainer in multi-GPU, single GPU, and CPU modes was added. CUDA integration was upgraded from CUDA 8 to CUDA 9 for several frameworks. February 28, 2018
Linux AMIs v3.0, plus introduction of MXNet Model Server, TensorFlow Serving, and TensorBoard Added tutorials for Conda AMIs with new model and visualization serving capabilities using MXNet Model Server v0.1.5, TensorFlow Serving v1.4.0, and TensorBoard v0.4.0. AMI and framework CUDA capabilities described in Conda and CUDA overviews. Latest release notes moved to January 25, 2018
Linux AMIs v2.0 Base, Source, and Conda AMIs updated with NCCL 2.1. Source and Conda AMIs updated with MXNet v1.0, PyTorch 0.3.0, and Keras 2.0.9. December 11, 2017
Two Windows AMI options added Windows 2012 R2 and 2016 AMIs released: added to AMI selection guide and added to release notes. November 30, 2017
Initial documentation release Detailed description of change with link to topic/section that was changed. November 15, 2017