Docker GPU Images: Add NVIDIA/apex to the cuda images with pytorch
# What does this PR do?
- Use cuda:10.2 image instead of 10.1 (to address version mismatch  warning with pytorch)
- Use `devel` version that is built on the `runtime` and includes headers and development tools (it was otherwise failing to build apex). For a description of the different flavors, see:  https://hub.docker.com/r/nvidia/cuda -> Overview of Images
- Download and build `apex` for pytorch. https://github.com/NVIDIA/apex#quick-start

## Docs
- https://github.com/NVIDIA/apex
- https://nvidia.github.io/apex/
- https://hub.docker.com/r/nvidia/cuda

## Who can review?
- @mfuntowicz co-authored the Dockerfiles in 71c87119
Hi @AdrienDS, 

Thanks for suggesting the changes.

Did you try building the image locally? I totally understand the motivation behind the use of the `-devel` layer parent, but I have concern regarding the final image size. Would it be possible for you to include the resulting size for th `devel` based image?

Otherwise look good for me!
<|||||>Hi @mfuntowicz It does increase the size, from 4.46GB (v3.3.1) to 6.53GB for `transformers-pytorch-gpu`. 

If it's too large, could we create a separate image ? (like: `transformers-pytorch-gpu-apex`)<|||||>Ok, that shouldn't hurt too much, let's go!

Thanks for the contribution 👍 