1

Hi to everybody and thanks in advance.

My goal is to use a GPU enabled container to execute the notebooks of Hands on Machine Learning book (2nd edition).
The idea is to use the GPU enabled container, maybe adding some imports and then committing to create a new image.

I checked the prerequisites as from https://github.com/NVIDIA/nvidia-docker/wiki/Installation-(version-2.0).

O.S. Ubuntu 18.04
Processor: Intel® Core™ i7-7700HQ CPU @ 2.80GHz × 8
Graphic card: GeForce GTX 1080/PCIe/SSE2
NVIDIA-SMI 418.87.00 and the graphic card is recognized,
docker Version: 19.03.5 API version: 1.40,
nvidia-docker2 is already the newest version (2.2.2-1),
nvidia-docker (the old version) is not present,

Executing:

docker pull tensorflow/tensorflow:2.0.0-gpu-py3-jupyter<br/><br/>
docker run -u $(id -u):$(id -g) -it --rm -v $(realpath ~/Projects/GDL/GDL_code):/tf/notebooks -p 8888:8888 tensorflow/tensorflow:2.0.0-gpu-py3-jupyter

the container starts regularly and I can use the the notebooks, but with no GPU support...

import tensorflow as tf
from tensorflow.python.client import device_lib

only the CPU is recognized...

I'm probably missing something of obvious ... I'm a newbie with docker and tensorflow...

Any help is appreciated!

motor
  • 21
  • 3
  • oops... missing --runtime=nvidia ... – motor Dec 11 '19 at 17:23
  • docker run --runtime=nvidia -u $(id -u):$(id -g) -it --rm -v $(realpath ~/Projects/GDL/GDL_code):/tf/notebooks -p 8888:8888 tensorflow/tensorflow:2.0.0-gpu-py3-jupyter – motor Dec 11 '19 at 17:25
  • If your problem is solved by setting `--runtime` flag, please write it as an answer below and mark it as a solution. – Szymon Maszke Dec 11 '19 at 20:40
  • Refer to this answer if your problem is still not resolved - https://stackoverflow.com/questions/25185405/using-gpu-from-a-docker-container/58432877#58432877 – Rohit Lal Dec 12 '19 at 06:27

1 Answers1

1

Sorry, missing --runtime=nvidia ...

docker run --runtime=nvidia -u $(id -u):$(id -g) -it --rm -v $(realpath ~/Projects/GDL/GDL_code):/tf/notebooks -p 8888:8888 tensorflow/tensorflow:2.0.0-gpu-py3-jupyter

Thanks anyway to everybody!

motor
  • 21
  • 3