An example to setup a docker container and jupyter server in a server and access from another host in LAN

docker_jupyter.sh

### An example to setup a docker container and jupyter server in a server and access from another host in LAN

## Pull docker image [Only first time]
sudo docker pull tensorflow/tensorflow:latest-gpu-jupyter


## Create and start docker container
sudo docker run --gpus all -it -p 192.168.x.x:8889:8888 -v /source/derectory/in/host:/dest/directory/in/container tensorflow/tensorflow:latest-gpu-jupyter bash

# Create and start docker container with current directory as source directory in host
sudo docker run --gpus all -it -p 192.168.x.x:8889:8888 -v ./:/fromhost tensorflow/tensorflow:latest-gpu-jupyter bash

# Command split:
# 
# --gpus all
#     To use all available gpus
# 
# -it
#     allocate a pseudo-TTY (terminal) and keep the container attached to your current terminal session
#     It allows you to interact with the container's shell or command-line interface
# 
# -p 192.168.x.x:8889:8888
#     Forward server from localhost:8888 in container to 192.168.x.x:8889 in LAN
# 
# -v /source/derectory/in/host:/dest/directory/in/container
#     Syncronize '/source/derectory/in/host' in host with '/dest/directory/in/container' in container
# 
# tensorflow/tensorflow:latest-gpu-jupyter
#     Name of docker image to be used
# 
# bash
#     No need to explain


## Start jupyter server
jupyter notebook --ip=0.0.0.0 --port=8888 --allow-root


## Fetch jupyter server url
http://192.168.30.151:8889/?token=<token-can-be-found-in-terminal-after-starting-server>

## Detach from container terminal without killing it
^P^Q<Enter>
#Ctrl+P Ctrl+Q ENTER

## Attach to a container
docker attach container_name