Installing TensorFlow with Python 3 on EC2 GPU Instances

Why not use the Tensorflow Docker images?<p>Or if you think they are too old, you can rebuild them manually, it will still be easier than installing all the dependencies manually.<p>There is also an easier way of downloading cuDNN v2 (there is no such thing as cuDNN v6.5 by the way): <a href="https:&#x2F;&#x2F;github.com&#x2F;NVIDIA&#x2F;nvidia-docker&#x2F;blob&#x2F;master&#x2F;ubuntu-14.04&#x2F;cuda&#x2F;7.0&#x2F;devel&#x2F;cudnn2&#x2F;Dockerfile#L13" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;NVIDIA&#x2F;nvidia-docker&#x2F;blob&#x2F;master&#x2F;ubuntu-1...</a>

This is a great guide for starting out, but how do I get TensorFlow on EC2 GPU instances in a more production-ready, reproducible way? Even the results of things like<p><pre><code> sudo apt-get update sudo apt-get upgrade -y sudo apt-get install -y build-essential git swig default-jdk zip zlib1g-dev </code></pre> are dependent on the point in time when the commands are issued. Also, 75 minutes is a long time to spin up an instance.

I&#x27;m using tensorflow with Python 3.5 on my machine, why does this say it doesn&#x27;t work with 3.5?