docker update
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# Use an existing image as the base
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FROM nvcr.io/nvidia/pytorch:22.06-py3
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# Add the current user to the image
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ARG USER_NAME=lhunor
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ARG USER_ID=11017
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ARG GROUP_NAME=guest
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ARG GROUP_ID=11000
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# Update the system and install required packages
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RUN apt-get update && apt-get upgrade -y && apt-get install -y sudo git apt-utils htop
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# Create a new group with the same GID as the host
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RUN groupadd --gid $GROUP_ID $GROUP_NAME
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# Create a new user with the same UID and GID as the host
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RUN useradd --uid $USER_ID --gid $GROUP_ID --shell /bin/bash --create-home $USER_NAME
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# don't require password with sudo, for convenience
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# not the safest thing to do, but hopefully okay inside the container
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RUN echo '%sudo ALL=(ALL) NOPASSWD:ALL' >> /etc/sudoers
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# Add the new user to the sudo group
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RUN usermod -aG sudo $USER_NAME
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# install conda stuff still as root
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RUN conda update -n base conda
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RUN conda install -c fvcore -c iopath -c conda-forge fvcore iopath -y
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RUN conda install -c bottler nvidiacub -y
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RUN conda install pytorch3d -c pytorch3d -y
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# Set the default user to the new user
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USER $USER_NAME
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ENV PATH="$PATH:/home/$USER_NAME/.local/bin"
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RUN pip install --upgrade pip
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COPY requirements.txt /tmp/
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RUN pip install --requirement /tmp/requirements.txt
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# defining the volumes that will be mounted
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VOLUME [ "/data-net" ]
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VOLUME [ "/data-local" ]
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VOLUME [ "/home-net" ]
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WORKDIR /workspace
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# Start the container with a bash shell
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CMD ["/bin/bash"]
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@@ -0,0 +1,20 @@
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services:
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lhunor_torch:
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image: lhunor_reconstruction:v1.13
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container_name: lhunor_reconstruction_v1.13
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ipc: host
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tty: true
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ulimits:
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memlock: -1
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stack: 67108864
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volumes:
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- '/home-net/lhunor:/home-net'
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- '/data-net/guest/lhunor/data:/data-net'
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#- '/data-fast/126-data1/lhunor/data:/data-local/126'
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#- '/data-fast/127-data1/lhunor/data:/data-local/127'
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- '/data-fast/128-data1/lhunor/data:/data-local/128'
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deploy:
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resources:
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reservations:
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devices:
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- capabilities: [gpu]
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@@ -0,0 +1,5 @@
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plotly
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scipy
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deodr
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pandas
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pytorch_msssim
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