fixed references
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		@@ -425,6 +425,7 @@ RUN pip install --no-cache-dir jupyter-tabnine==1.0.2  && \
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RUN fix-permissions $CONDA_DIR
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					RUN fix-permissions $CONDA_DIR
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RUN conda install -c conda-forge jupyter_contrib_nbextensions && \
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					RUN conda install -c conda-forge jupyter_contrib_nbextensions && \
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  conda install -c conda-forge jupyter_nbextensions_configurator && \
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					  conda install -c conda-forge jupyter_nbextensions_configurator && \
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					  conda install -c conda-forge rise && \
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  jupyter nbextension enable codefolding/main
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					  jupyter nbextension enable codefolding/main
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RUN jupyter labextension install @ijmbarr/jupyterlab_spellchecker
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					RUN jupyter labextension install @ijmbarr/jupyterlab_spellchecker
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							@@ -113,3 +113,4 @@ venv.bak/
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# Added config to hide hash of changed password
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					# Added config to hide hash of changed password
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src/jupyter_notebook_config.json
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					src/jupyter_notebook_config.json
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.idea
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					.idea
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					/Deployment-notes.md
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@@ -1,38 +0,0 @@
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# Deployment Notes
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## Push image with tag to Dockerhub
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Based on [this](https://ropenscilabs.github.io/r-docker-tutorial/04-Dockerhub.html) tutorial
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with the tag `v1.0_cuda-10.1_ubuntu-18.04`:
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```bash
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# on il048:
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cd ~/Documents/projects/GPU-Jupyter/gpu-jupyter
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git pull
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bash generate_Dockerfile.sh
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bash start-local -p 1234
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docker image ls
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docker tag [IMAGE ID] cschranz/gpu-jupyter:v1.0_cuda-10.1_ubuntu-18.04
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docker push cschranz/gpu-jupyter:v1.0_cuda-10.1_ubuntu-18.04
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docker save cschranz/gpu-jupyter > ../gpu-jupyter_tag-v1.0_cuda-10.1_ubuntu-18.04.tar
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```
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Then, the new tag is available on [Dockerhub](https://hub.docker.com/repository/docker/cschranz/gpu-jupyter/tags).
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## Deployment in the swarm
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The GPU-Jupyter instance for deployment, that has swarm files and changed pw is
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in `/home/iotdev/Documents/projects/dtz/src/gpu-jupyter`
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```bash
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# on il048:
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cd /home/iotdev/Documents/projects/dtz/src/gpu-jupyter
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git pull
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bash generate_Dockerfile.sh
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bash add-to-swarm-with-defaults.sh
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```
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Then, the service will be available with data stored in `data` 
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on [192.168.48.48:8848](http://192.168.48.48:8848) with our password.
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							@@ -44,7 +44,7 @@ directly on the host node), you can run these commands to start the jupyter note
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docker-compose (internally):
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					docker-compose (internally):
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  ```bash
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					  ```bash
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  ./generate_Dockerfile.sh
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					  ./generate-Dockerfile.sh
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  docker build -t gpu-jupyter .build/
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					  docker build -t gpu-jupyter .build/
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  docker run -d -p [port]:8888 gpu-jupyter
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					  docker run -d -p [port]:8888 gpu-jupyter
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  ``` 
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					  ``` 
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@@ -53,7 +53,7 @@ Alternatively, you can configure the environment in `docker-compose.yml` and run
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this to deploy the `GPU-Jupyter` via docker-compose (under-the-hood):
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					this to deploy the `GPU-Jupyter` via docker-compose (under-the-hood):
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  ```bash
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					  ```bash
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  ./generate_Dockerfile.sh
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					  ./generate-Dockerfile.sh
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  ./start-local.sh -p 8888  # where -p stands for the port of the service
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					  ./start-local.sh -p 8888  # where -p stands for the port of the service
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  ```
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					  ```
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@@ -133,7 +133,7 @@ networks:
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Finally, *GPU-Jupyter* can be deployed in the Docker Swarm with the shared network, using:
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					Finally, *GPU-Jupyter* can be deployed in the Docker Swarm with the shared network, using:
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```bash
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					```bash
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./generate_Dockerfile.sh
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					./generate-Dockerfile.sh
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./add-to-swarm.sh -p [port] -n [docker-network] -r [registry-port]
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					./add-to-swarm.sh -p [port] -n [docker-network] -r [registry-port]
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# e.g. ./add-to-swarm.sh -p 8848 -n elk_datastack -r 5001
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					# e.g. ./add-to-swarm.sh -p 8848 -n elk_datastack -r 5001
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```
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					```
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@@ -190,7 +190,7 @@ and in the `Dockerfile.pytorch` the line:
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Then re-generate and re-run the image, as closer described above:
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					Then re-generate and re-run the image, as closer described above:
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```bash
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					```bash
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./generate_Dockerfile.sh
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					./generate-Dockerfile.sh
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./start-local.sh -p [port]:8888  
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					./start-local.sh -p [port]:8888  
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```
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					```
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@@ -201,13 +201,13 @@ submodule within `.build/docker-stacks`. Per default, the head of the commit is
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To update the generated Dockerfile to a specific commit, run:
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					To update the generated Dockerfile to a specific commit, run:
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```bash
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					```bash
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./generate_Dockerfile.sh --commit c1c32938438151c7e2a22b5aa338caba2ec01da2
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					./generate-Dockerfile.sh --commit c1c32938438151c7e2a22b5aa338caba2ec01da2
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```
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					```
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To update the generated Dockerfile to the latest commit, run:
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					To update the generated Dockerfile to the latest commit, run:
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```bash
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					```bash
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./generate_Dockerfile.sh --commit latest
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					./generate-Dockerfile.sh --commit latest
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```
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					```
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A new build can last some time and may consume a lot of data traffic. Note, that the latest version may result in
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					A new build can last some time and may consume a lot of data traffic. Note, that the latest version may result in
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@@ -103,5 +103,5 @@ echo "COPY jupyter_notebook_config.json /etc/jupyter/"  >> $DOCKERFILE
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#cp $(find $(dirname $DOCKERFILE) -type f | grep -v $STACKS_DIR | grep -v .gitkeep) .
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					#cp $(find $(dirname $DOCKERFILE) -type f | grep -v $STACKS_DIR | grep -v .gitkeep) .
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echo "GPU Dockerfile was generated sucessfully in file ${DOCKERFILE}."
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					echo "GPU Dockerfile was generated successfully in file ${DOCKERFILE}."
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echo "Run 'bash run_Dockerfile.sh -p [PORT]' to start the GPU-based Juyterlab instance."
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					echo "Run 'bash start-local.sh -p [PORT]' to start the GPU-based Juyterlab instance."
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