Closed JGuillaumin closed 7 years ago
@JGuillaumin It used the GPU on my end. However I encountered an issue where CuDNN wasn't detected so I fixed that. The gpu files were combined and it's now just Dockerfile.gpu
.
What commands are you running?
I ran:
docker build -f Dockerfile.gpu -t dom/sk .
and
nvidia-docker run -it --rm -p 8888:8888 -v `pwd`:/src dom/sk python -c "import tensorflow"
The output from this should be something like
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcurand.so locally
Hi,
I built an image with
Dockerfile.gpu-ubuntu-16.04
andDockerfile.gpu
from this repo. No problem during building, but it doesn't use the GPU when I launch it withnvidia-docker
.I tried with this Dockerfile: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/docker/Dockerfile.gpu . Well, it runs on my GPU, but it works with python 2.7. When I try to mix the two dockerfiles, to create an image that uses Python 3.5, it failed during building.
Someone found or tried some solutions to run an image with Tensorflow & Keras on python3.5 ?
Configuration : Laptop ASUS R415U GTX 940MX (drivers : 370.28) Ubuntu 16.04 kernel : 4.4.0-59-generic Docker version 1.12.6, build 78d1802