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Dockerfile

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# Use the NVIDIA CUDA base image with CUDA 12.5.1 and cuDNN on Ubuntu 22.04
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FROM nvidia/cuda:12.2.2-cudnn8-runtime-ubuntu22.04
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ENV DEBIAN_FRONTEND=noninteractive
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# Install Python, pip, and bash
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RUN apt-get update && apt-get install -y \
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python3 \
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# Set Python3 as the default python
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RUN ln -s /usr/bin/python3 /usr/bin/python
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# Set the timezone
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ENV TZ=Europe/Berlin
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# Install tzdata and other packages
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RUN apt-get update && \
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apt-get install -y --no-install-recommends tzdata curl vim && \
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ln -fs /usr/share/zoneinfo/$TZ /etc/localtime && \
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dpkg-reconfigure --frontend noninteractive tzdata && \
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apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
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RUN apt-get update && apt-get install -y \
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bash git-all unzip \
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bash git-all unzip software-properties-common\
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libgl1-mesa-glx libglib2.0-0 \
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build-essential libopenmpi-dev \
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&& rm -rf /var/lib/apt/lists/*
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# Install pip, JupyterLab, and attrs
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RUN pip install --upgrade pip
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RUN pip install --upgrade awscli attrs jupyterlab jupyterlab-git
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RUN pip install --upgrade opencv-python flake8 matplotlib pytest shapely tqdm
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RUN pip install --upgrade opencv-python opencv-python torch torch_geometric torchtyping wandb x-transformers
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RUN pip install --upgrade flake8 matplotlib pytest shapely tqdm
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RUN pip install --upgrade opencv-python torch torch_geometric torchtyping wandb x-transformers
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# Expose port 8888 for JupyterLab
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EXPOSE 8888

build-tag-push.sh

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#! /bin/bash
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docker build -t my-gradient-notebook .
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docker tag my-gradient-notebook manavmahan/pytorch-cuda-notebook:latest
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docker push manavmahan/pytorch-cuda-notebook:latest
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docker tag my-gradient-notebook manavmahan/pytorch-cuda-notebook:main
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docker push manavmahan/pytorch-cuda-notebook:main

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