Features of the DLAMI
Preinstalled Frameworks
There are currently two primary flavors of the DLAMI with other variations related to the operating system (OS) and software versions:
-
Deep Learning AMI with Conda - frameworks installed separately using
conda
packages and separate Python environments -
Deep Learning Base AMI - no frameworks installed; only NVIDIA CUDA
and other dependencies
The Deep Learning AMI with Conda uses conda
environments to isolate each framework, so you can
switch between them at will and not worry about their dependencies conflicting.
This is the full list of supported frameworks by Deep Learning AMI with Conda:
-
Apache MXNet (Incubating)
-
PyTorch
-
TensorFlow 2
Note
We no longer include the CNTK, Caffe, Caffe2, Theano, Chainer, or Keras Conda environments in the Amazon Deep Learning AMI starting with the v28 release. Previous releases of the Amazon Deep Learning AMI that contain these environments will continue to be available. However, we will only provide updates to these environments if there are security fixes published by the open source community for these frameworks.
Preinstalled GPU Software
Even if you use a CPU-only instance, the DLAMI will have NVIDIA CUDA
For more information on CUDA Installation, see the CUDA Installations and Framework Bindings.
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.