What is the best way to run TensorFlow 2.0 with AWS Sagemeker?
As of today (Aug 7th, 2019) AWS does not provide TensorFlow 2.0 SageMaker containers, so my understanding is that I need to build my own.
What is the best Base image to use? Example Dockerfile?
EDIT: Amazon SageMaker does now support TF 2.0 and higher.
Original answer
Here is an example Dockerfile that uses the underlying SageMaker Containers library (this is what is used in the official pre-built Docker images):
For more information on this approach, see https://docs.aws.amazon.com/sagemaker/latest/dg/build-container-to-train-script-get-started.html
Update on 10 nov 2019:
There is now a way to use Tensorflow 2 in SageMaker, event though there is no shortcut to start TF 2 directly from SageMaker console.
Start a conda Python3 Kernel
Make some updates (one in each code cell):
Given the doc, this will install in
$HOME
.You now can use TF 2 in your instance. This only needs to be done once, as long as the instance remains up.
To test, just run in the next cell:
You should see
2.0.0
or higher.As of now, the best image that you can use to build Tensorflow 2.0 is 2.0.0b1, which is the latest version of Tensorflow 2.0(image) that is available now.Please find the link here. You also have an image 2.0.0b1-py3, which comes with Python3 (3.5 for Ubuntu 16-based images; 3.6 for Ubuntu 18-based images).
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