Build a docker image for openchatkit #40

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1. csris commented on Mar 14, 2023

   

   csris

   on Mar 14, 2023

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   Thanks for the feature request. This is a great idea. Will put it on the roadmap.
2. rpj09 commented on Mar 14, 2023

   

   rpj09

   on Mar 14, 2023

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   Hey @Jonuknownothingsnow i am new to open source . and it would be very happy to work on this idea under your guidance
3. kailust commented on Mar 15, 2023

   

   kailust

   on Mar 15, 2023

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   Dockerfile

   # Base image
   FROM ubuntu:20.04
   
   # Set working directory
   WORKDIR /app
   
   # Update and install required packages
   RUN apt-get update && \
       apt-get install -y git-lfs wget && \
       rm -rf /var/lib/apt/lists/*
   
   # Download and install Miniconda
   RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
       bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/conda && \
       rm Miniconda3-latest-Linux-x86_64.sh
   
   # Set conda to automatically activate base environment on login
   RUN echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc && \
       echo "conda activate base" >> ~/.bashrc
   
   # Create OpenChatKit environment
   COPY environment.yml .
   RUN conda env create -f environment.yml
   
   # Install Git LFS
   RUN git lfs install
   
   # Copy OpenChatKit code
   COPY . .
   
   # Prepare GPT-NeoX-20B model
   RUN python pretrained/GPT-NeoX-20B/prepare.py
   
   # Set entrypoint to bash shell
   ENTRYPOINT ["/bin/bash"]
   

   Build the Docker image using the following command:

   docker build -t openchatkit .
   

   Run the Docker container using the following command:

   docker run -it openchatkit
   

   This will start a new bash shell in the container.
   Activate the OpenChatKit environment by running the following command:

   conda activate OpenChatKit
   

   You should now be able to use the OpenChatKit code and run the prepare.py script.

   🚀React with 🚀3Reacted by Matthew Francis Brunetti, Joen Wallenstrøm (UnLogick) and theycallmeloki
4. csris

   assigned

   rpj09

   on Mar 18, 2023
5. csris commented on Mar 18, 2023

   

   csris

   on Mar 18, 2023

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   As I mentioned in the PR, both the pretrained model and datasets can be quite large.

   $ du -sh data/* pretrained/GPT-NeoX-20B/
   172G    data/OIG
   238M    data/OIG-moderation
   38G     data/wikipedia-3sentence-level-retrieval-index
   39G     pretrained/GPT-NeoX-20B/
   

   The Dockerfile above bakes the 39GB pretrained model into the image. In my opinion, it would be better to download the pretrained model into a bind mount when the container starts. The image would be much smaller and the bind mount persists the model across container restarts.
6. rpj09 commented on Mar 19, 2023

   

   rpj09

   on Mar 19, 2023

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   As I mentioned in the PR, both the pretrained model and datasets can be quite large.

   $ du -sh data/* pretrained/GPT-NeoX-20B/
   172G    data/OIG
   238M    data/OIG-moderation
   38G     data/wikipedia-3sentence-level-retrieval-index
   39G     pretrained/GPT-NeoX-20B/
   

   The Dockerfile above bakes the 39GB pretrained model into the image. In my opinion, it would be better to download the pretrained model into a bind mount when the container starts. The image would be much smaller and the bind mount persists the model across container restarts.

   Sure i will try to do it
7. xsanz commented on Apr 22, 2023

   

   xsanz

   on Apr 22, 2023

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   Hello,

   I'm just starting with OpenChat, I was checking to use Docker and I found your Dockerfile.

   One question, for training the model, I understand cuda + nvidia are used if available?

   If that yes, yesterday I found this, maybe useful https://blog.roboflow.com/nvidia-docker-vscode-pytorch/
   Looks like there are docker-nvidia accelerated containers nvidia/cuda:11.0.3-base-ubuntu20.04 ready to be used.
   (Note: Because I use docker-compose I had to update to a 1.28.0+ version to configure of '--gpus all' parameter)

   Thank you

   👍React with 👍2Reacted by orangetin and Joen Wallenstrøm (UnLogick)
8. xsanz commented on Apr 23, 2023

   

   xsanz

   on Apr 23, 2023

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   Hello there,

   Just mention that I had issues building the environment with package netifaces, that I solved updating environment.yml file from netifaces===0.11.0 to netifaces2==0.0.16

   Thank you
9. orangetin commented on Apr 23, 2023

   

   orangetin

   on Apr 23, 2023

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   Hello there,

   Just mention that I had issues building the environment with package netifaces, that I solved updating environment.yml file from netifaces===0.11.0 to netifaces2==0.0.16

   Thank you

   This can be fixed by installing gcc. On Ubuntu, you'd run sudo apt install gcc. That should fix your error!

   👍React with 👍2Reacted by xsanz and Joen Wallenstrøm (UnLogick)
10. orangetin commented on Apr 25, 2023

    

    orangetin

    on Apr 25, 2023

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    If that yes, yesterday I found this, maybe useful https://blog.roboflow.com/nvidia-docker-vscode-pytorch/ Looks like there are docker-nvidia accelerated containers nvidia/cuda:11.0.3-base-ubuntu20.04 ready to be used. (Note: Because I use docker-compose I had to update to a 1.28.0+ version to configure of '--gpus all' parameter)

    Thanks for the great resource @xsanz! I was able to get the model loaded onto the GPU in docker using those instructions

    👍React with 👍2Reacted by xsanz and Joen Wallenstrøm (UnLogick)
11. mlaug commented on May 6, 2023

    

    mlaug

    on May 6, 2023

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    the conda binary was not found during my docker build. If anyone runs into this issue, I had set the PATH correctly before trying to run conda

    ENV PATH=/opt/conda/bin/:$PATH

    👍React with 👍1Reacted by Joen Wallenstrøm (UnLogick)