davidelanz/jupytorch repository overview

⁠Jupytorch | Docker image enabled with Pytorch and Jupyter

Repository for the davidelanz/jupytorch⁠ docker image. It provides a quick set up for Pytorch and Jupyter Lab with Docker.

	Features
	The image supports nbdev⁠ paradigm (by fast.ai), allowing you to develop python libraries directly in Jupyter Notebooks
	The image comes with jupyterlab_code_formatter⁠ already installed
	The image comes with LSP Python language server for JupyterLab⁠ already installed

⁠Mount from DockerHub

Download the image from davidelanz/jupytorch⁠, then mount the container (the image exposes JupyterLab on the 8888 port):

docker run -p CONTANER_PORT:8888 -v EXTERNAL_FOLDER:/workspace --name CONTAINER_NAME davidelanz/jupytorch:TAG

Your workspace will be available at localhost:CONTANER_PORT⁠.

Supported tags:

• docker pull davidelanz/jupytorch:cpu
• docker pull davidelanz/jupytorch:gpu-cuda10.1-cudnn7
• docker pull davidelanz/jupytorch:gpu-cuda10.1-cudnn8
• docker pull davidelanz/jupytorch:gpu-cuda10.2-cudnn7
• docker pull davidelanz/jupytorch:gpu-cuda10.2-cudnn8
• docker pull davidelanz/jupytorch:gpu-cuda11.1.1-cudnn8

⁠Build Custom CPU version from GitHub

The CPU version is directly built on the ubuntu18.04 docker image.

$ git clone https://github.com/davidelanz/jupytorch-docker
$ cd jupytorch-docker/cpu

# choose different PYTHON_VERSION and PYTORCH_VERSION arguments if needed

$ docker build . -t jupytorch/cpu \
    --build-arg PYTHON_VERSION=### \
    --build-arg PYTORCH_VERSION=###

⁠Build Custom GPU version from GitHub

The GPU version is directly built on the nvidia/cuda:{CUDA_VERSION}-cudnn{CUDNN_VERSION}-runtime-ubuntu18.04 docker image.

$ git clone https://github.com/davidelanz/jupytorch-docker
$ cd jupytorch-docker/gpu

# choose different PYTHON_VERSION, PYTORCH_VERSION, CUDA_VERSION, and CUDNN_VERSION arguments if needed

$ docker build . -t jupytorch/cpu \
    --build-arg PYTHON_VERSION=### \
    --build-arg PYTORCH_VERSION=### \
    --build-arg CUDA_VERSION=### \
    --build-arg CUDNN_VERSION=###