Installing TensorFlow with Python 3 on EC2 GPU Instances(eatcodeplay.com) |
Installing TensorFlow with Python 3 on EC2 GPU Instances(eatcodeplay.com) |
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...
[1] for example: Ubuntu 14.04 (HVM) public ami, ami-06116566
$ 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.
sudo apt-get update
sudo apt-get upgrade -y
sudo apt-get install -y build-essential git swig default-jdk zip zlib1g-dev
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'll give 3.5 a go in the next couple days and update the guide as necessary. Thanks!