Machine Learning Environment

GPU-Enabled Development Environment using Docker

Included

• JupyterLab

• TensorFlow with GPU support

• CUDA 9.0 + cuDNN 7.0

Requirments:

• nvidia-docker

For nvidia-docker to work see the following:

• Prerequisites / NVIDIA driver / Supported Version / Docker

Build

git clone https://github.com/CR351/ML-Environment

cd ML-Environment

sudo docker build -t ml-env .

Run

Change path "/host/dir" to local work directory

sudo nvidia-docker run -it -p 6006:6006 -p 8888:8888 -v /host/dir:/home ml-env 

Once inside the container

Jupyterlab

jupyter-lab --allow-root

http://localhost:8888/lab

Tensorboard

tensorboard --logdir=/tmp/

http://localhost:6006/