Hi CooperativeFox72

But my docker image has all my code and all the packages it needed I don't understand why the agent need to install all of those again? (edited)

So based on the docker file you previously posted, I think all your python packages are actually installed on the "appuser" and not as system packages.
Basically remove the "add user" part and the --user from the pip install.
For example:
` FROM nvidia/cuda:10.1-cudnn7-devel

ENV DEBIAN_FRONTEND noninteractive
RUN apt-get update && apt-get install -y
    python3-opencv ca-certificates python3-dev git wget sudo ninja-build
RUN ln -sv /usr/bin/python3 /usr/bin/python

WORKDIR /root/

RUN wget &&
    python3 get-pip.py &&
    rm get-pip.py

install dependencies

See for other options if you use a different version of CUDA

RUN pip install tensorboard cmake   # cmake from apt-get is too old
RUN pip install torch==1.8 torchvision==0.9 -f

RUN pip install 'git+ '

install detectron2

RUN git clone detectron2_repo

set FORCE_CUDA because during docker build cuda is not accessible

ENV FORCE_CUDA="1"

This will by default build detectron2 for all common cuda architectures and take a lot more time,

because inside docker build, there is no way to tell which architecture will be used.

ARG TORCH_CUDA_ARCH_LIST="Kepler;Kepler+Tesla;Maxwell;Maxwell+Tegra;Pascal;Volta;Turing"
ENV TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST}"

RUN pip install -e detectron2_repo

Set a fixed model cache directory.

ENV FVCORE_CACHE="/tmp" `