Deep Learning AMI Ubuntu Version

The Deep Learning AMI is a base Ubuntu image provided by Amazon Web Services for use on Amazon Elastic Compute Cloud(Amazon EC2).It is designed to provide a stable, secure, and high performance execution environment for deep learning applications running on Amazon EC2. It includes popular deep learning frameworks, including MXNet, Caffe, Caffe2, TensorFlow, Theano, CNTK, Torch and Keras as well as packages that enable easy integration with AWS, including launch configuration tools and many popular AWS libraries and tools. It also includes Anaconda Data Science Platform for Python2 and Python3. The Deep Learning AMI is provided at no additional charge to Amazon EC2 users.The AMI Ids for the Deep Learning Ubuntu AMI are the following:us-east-1: ami-06e80e7c us-east-2: ami-35e9cb50 us-west-2: ami-d6ee1dae eu-west-1: ami-cd67a4b4 ap-southeast-2: ami-9403e4f6 ap-northeast-1: ami-ff995499 ap-northeast-2: ami-5238e33c Release tags/Branches used for the DW Frameworks:MXNet 0.11.0TensorFlow 1.3.0Keras 1.2.2 (DMLC fork with MXNet 0.11 support)Caffe 1.0Caffe2 0.8.0CNTK 2.0Theano 0.9.0Torch (master branch)Caffe2 0.8.0 no longer supports g2.xxx instances. You can get Caffe2 0.7.0 on the older AMI version 2.2_Aug2017. Check the AMI release notes at following link: http://docs.aws.amazon.com/mxnet/latest/dg/appendix-ami-release-notes.html


    Customer Rating

    (7 Customer Reviews)
    7 reviews
    5 star:

    (1)
    4 star:

    (1)
    3 star:

    (0)
    2 star:

    (0)
    1 star:

    (5)

    Latest Version

    2.3_Sep2017 (Other available versions)


    Operating System

    Linux/Unix, Ubuntu 16.04


    Delivery Method

    64-bit Amazon Machine Image (AMI) (Read more)



    AWS Services Required

    Amazon EC2, Amazon EBS


    Highlights

    • Used Ubuntu 16.04 (ami-cd0f5cb6) as the base AMI with CUDA 8 support
    • Framework upgrades for MXNet (v0.11.0), TensorFlow (v1.3.0) and Caffe2(v0.8.0). Please note that Caffe2 is no longer compatible with the g2.xxx instances. Read Product Description below.
    • 7 Deep Learning Frameworks - contains the most popular Deep Learning Frameworks(MXNet, Caffe, Caffe2, Tensorflow, Theano, Torch and CNTK)

    Product Description

    The Deep Learning AMI is a base Ubuntu image provided by Amazon Web Services for use on Amazon Elastic Compute Cloud(Amazon EC2).It is designed to provide a stable, secure, and high performance execution environment for deep learning applications running on Amazon EC2. It includes popular deep learning frameworks, including MXNet, Caffe, Caffe2, TensorFlow, Theano, CNTK, Torch and Keras as well as packages that enable easy integration with AWS, including launch configuration tools and many popular AWS libraries and tools. It also includes Anaconda Data Science Platform for Python2 and Python3. The Deep Learning AMI is provided at no additional charge to Amazon EC2 users.

    The AMI Ids for the Deep Learning Ubuntu AMI are the following:
    us-east-1: ami-06e80e7c
    us-east-2: ami-35e9cb50
    us-west-2: ami-d6ee1dae
    eu-west-1: ami-cd67a4b4
    ap-southeast-2: ami-9403e4f6
    ap-northeast-1: ami-ff995499
    ap-northeast-2: ami-5238e33c

    Release tags/Branches used for the DW Frameworks:
    MXNet 0.11.0
    TensorFlow 1.3.0
    Keras 1.2.2 (DMLC fork with MXNet 0.11 support)
    Caffe 1.0
    Caffe2 0.8.0
    CNTK 2.0
    Theano 0.9.0
    Torch (master branch)

    Caffe2 0.8.0 no longer supports g2.xxx instances. You can get Caffe2 0.7.0 on the older AMI version 2.2_Aug2017. Check the AMI release notes at following link: http://docs.aws.amazon.com/mxnet/latest/dg/appendix-ami-release-notes.html

    Product Details

    • Version: 2.3_Sep2017
    • Available on AWS Marketplace Since: 02/10/2017

    Usage Instructions

    To connect to the operating system, use SSH and the username ubuntu. You can find additional information in the README. /home/ubuntu/src/README.md

    Support Details

    Deep Learning AMI Ubuntu Version

    Support is available through forums, technical FAQs and the Service Help Dashboard. Paid support is available.

    https://forums.aws.amazon.com/forum.jspa?forumID=30

    AWS Infrastructure

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services. Learn more

    Refund Policy

    We do not currently support refunds, but you can cancel at any time.

    End User License Agreement

    By subscribing to this product you agree to terms and conditions outlined in the product End User License Agreement (EULA).

    Continue

    You will have an opportunity to review your order before launching or being charged.

    Pricing Information

    Use the Region dropdown selector to see software and infrastructure pricing information for the chosen AWS region.

    For Region

    Free Tier Eligible
    EC2 charges for Micro instances are free for up to 750 hours a month if you qualify for the AWS Free Tier.
    Additional Taxes May Apply
     

    Pricing Details

    Software pricing is based on your chosen options, such as subscription term and AWS region. Infrastructure prices are estimates only. Final prices will be calculated according to actual usage and reflected on your monthly report.
    Software Pricing
    The data below shows pricing per instance for services hosted in .
    Infrastructure Pricing
    Total hourly price will vary by instance type and EC2 region. Click here for full EC2 pricing

    Recent Product Reviews

    09/18/2017

    Getting started REALLY required

    I need to get the following: - CUDA (8.0) - cuDNN (6) - Tensorflow (latest) It is extremely unclear...

    Read more

    09/13/2017

    Deep Learning AMI Ubuntu: Free tier or not Free tier

    Tried to launch the instance in subj, which is marked as 'free tier eligible' and got the message - '...not...

    Read more

    08/28/2017

    Got Tensorflow working via Tensorflow3

    Per the other reviews, the default tensorflow in ~/src/tensorflow was problematic. However, we've had...

    Read more

    08/10/2017

    Tensorflow does not work with Jupyter

    import tensorflow fails from a jupyter notebook in both python2 and python3. It was successful on the...

    Read more

    08/09/2017

    Cannot load tensorflow

    Got it up and running and ran "import tensorflow" -- no luck though. Traceback (most recent call last): File "/home/ubuntu/deployments/data-pipelines/scratch/function_test.py", line 1, in <module> import tensorflow as tf File "/usr/local/lib/python2.7/dist-packages/tensorflow/__init__.py", line 24, in <module> from tensorflow.python import * File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/__init__.py", line 49, in <module> from tensorflow.python import pywrap_tensorflow File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 52, in <module> raise ImportError(msg) ImportError: Traceback (most recent call last): File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 41, in <module> from tensorflow.python.pywrap_tensorflow_internal import * File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>...

    Read more

    Create Your Own Review