The steps to follow are here.
In this post, I am not explaining all the bits and pieces on how to install, I am trying to avoid the confusion regarding what to follow.
Here is the main dependency, If you need to train tensorflow model with NVIDIA DIGITS, you need to get DIGITS 6. If you have DIGITS 5 installed, It won’t detect tensorflow. At the time of writing, unlike installing DIGITS 5, there are no binaries provided by NVIDIA to install DIGITS 6. You need to either install using docker or compile and install from source. I tried installing from docker, later I figured out that unless you are already familiar with docker, you are going to spend hell a lot of time trying to understand docker itself and its usage. Then there is nvidia-docker, which is the one actually needed for NVIDIA DIGITS 6. I tried for some time and realised that it is not required for me since I own the machine and I am the only person using it. I really am not ready to spend time on going through docker pain at this point of time.
Even though I am not a fan of compiling and installing, looks like that’s the only way. It is going to take some time and, you may need to fix some build failures, dependencies, stack-overflowing, googling etc. I followed the installation instructions from DIGITS github page.
Long story short, you need to,
- Remove DIGITS 5 ( check here how to list and remove packages)
- compile and install Caffe (can not skip this, it is a dependency for DIGITS 6)
- compile and install Torch (not a requirement but let’s keep it)
- compile and install tensorflow_gpu (I had this already, so I skipped)
- compile and install DIGITS 6
Make sure you add this variables to ~/.bashrc
export DIGITS_ROOT=~/digits export CAFFE_ROOT=~/caffe export TORCH_ROOT=~/torch
The digits server can be invoked by ‘digits-devserver &‘. By default the service will be active at http://localhost:5000/
If everything goes fine, when you create a new model in DIGITS you can see the frameworks.