After failing to ssh to instance I created on AWS I created one in Azure(Ubuntu 17.04, NC6 size), installed what is needed and eventually able to make Jupyter Notebook run successfully. While trying to run Lesson1 it was failing when running the following snippet.
import utils; reload(utils)
from utils import plots
While researching I found a clue that says since Ubuntu 17.04 is latest it might not work properly due to lack of support for Nvidia. So I build another server(Ubuntu Server 16.04) and this time it complained about CV which I installed(openCV). Now when I run the above code it doesn’t succeed or fail(what is the expected behavior ??)
Not sure what to do next. I am new to Deep learning and linux world and I am afraid I have reached the limit of my researching skills and it is becoming very frustrating. Any help to pass this hurdle and run Lesson1 successfully is appreciated.
Below is nvidia-smi output.
±----------------------------------------------------------------------------+
| NVIDIA-SMI 384.66 Driver Version: 384.66 |
|-------------------------------±---------------------±---------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla K80 Off | 0000FA46:00:00.0 Off | 0 |
| N/A 31C P0 70W / 149W | 0MiB / 11439MiB | 0% Default |
±------------------------------±---------------------±---------------------+
±----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
±----------------------------------------------------------------------------+