Deep Learning AMI
Developer Guide

Features of the DLAMI

Preinstalled Frameworks

There are currently three primary flavors of the DLAMI with other variations related to the operating system (OS) and software versions:

The new Deep Learning AMI with Conda uses Anaconda environments to isolate each framework, so you can switch between them at will and not worry about their dependencies conflicting. The Deep Learning AMI with Source Code has all of the deep learning frameworks installed into the same Python environment, along with the frameworks' source.

For more information on selecting the best DLAMI for you, take a look at Getting Started.

This is the full list supported frameworks between Deep Learning AMI with Conda and Deep Learning AMI with Source Code:

  • Apache MXNet

  • Caffe

  • Caffe2

  • CNTK

  • Keras

  • PyTorch

  • TensorFlow

  • Theano**

  • Torch*


* Only available on the Deep Learning AMI with Source Code.

** Theano is being phased out, as it is no longer an active project.

Preinstalled GPU Software

Even if you use a CPU-only instance, the DLAMI will have NVIDIA CUDA and NVIDIA cuDNN. The installed software is the same regardless of the instance type. Keep in mind that GPU-specific tools only work on an instance that has at least one GPU. More information on this is covered in the Selecting the Instance Type for DLAMI.

Model Serving and Visualization

Deep Learning AMI with Conda comes preinstalled with two kinds of model servers, one for MXNet and one for TensorFlow, as well as TensorBoard, for model visualizations.