Hacker News Reader

Why not use the Tensorflow Docker images?

Or if you think they are too old, you can rebuild them manually, it will still be easier than installing all the dependencies manually.

There is also an easier way of downloading cuDNN v2 (there is no such thing as cuDNN v6.5 by the way): https://github.com/NVIDIA/nvidia-docker/blob/master/ubuntu-1...

View on HN

Is running the docker image on a fresh standard AMI [1] all it takes to get a working tensorflow backed by the GPU? There is nothing you need to install on the host OS?

[1] for example: Ubuntu 14.04 (HVM) public ami, ami-06116566

You need the NVIDIA drivers and the nvidia-docker plugin.

$ docker-machine create --driver amazonec2 --amazonec2-instance-type g2.2xlarge ...

$ docker-machine ssh <host> # install the NVIDIA driver and nvidia-docker-plugin

$ eval `docker-machine env <host>`

$ ssh-add ~/.docker/machine/machines/<host>/id_rsa

$ NV_HOST="ssh://ubuntu@<ip>:" nvidia-docker run mybuild/tensorflow

Step 2 can be skipped if you use a custom AMI.

Reply on news.ycombinator.com