You'll need to run this with a Docker capable host computer, installation support is provided on Ubuntu.
install-docker.sh -- this will get Docker up and running
Now you can get a container ready with:
docker build --tag keras-cpu .
docker run -p 8888:8888 --volume $(pwd):/src keras-cpu
gpu/install-nvidia-docker.sh -- this requires you have a NVIDIA graphics card as well as the current driver.
If all is well at this point, you will see an inventory of your graphics cards such as:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 390.77 Driver Version: 390.77 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 TITAN V Off | 00000000:03:00.0 Off | N/A |
| 37% 53C P0 38W / 250W | 0MiB / 12066MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 TITAN V Off | 00000000:04:00.0 Off | N/A |
| 33% 48C P0 37W / 250W | 0MiB / 12066MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
Now you can get a container ready with:
docker build --tag keras-gpu ./gpu
nvidia-docker run -p 8888:8888 --volume $(pwd):/src keras-gpu