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# Obraz ubuntu latest
FROM ubuntu:latest
# Instalacja niezbędnych bibliotek
RUN apt update
RUN apt-get update
RUN apt install -y figlet
RUN export PATH = ”$PATH :/usr/local/bin/python”
RUN apt install python3-pip -y
RUN apt install unzip -y
RUN pip3 install kaggle
RUN pip3 install pandas
RUN pip3 install torch
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RUN pip3 install torchvision
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RUN pip3 install jovian
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RUN pip3 install matplotlib
RUN pip3 install seaborn
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RUN pip3 install sklearn
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RUN pip3 install sacred
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RUN pip3 install numpy
RUN pip3 install wheel --no-deps -U
RUN pip3 install GitPython
RUN pip3 install pymongo
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RUN pip3 install mlflow
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# Przygotowanie kaggle
RUN mkdir ~/.kaggle/
RUN echo '{"username":"sebastianwalesa","key":"c879e3806be4cd6ade7aa10ea81d4cfe"}' > ~/.kaggle/kaggle.json
# Stwórzmy w kontenerze (jeśli nie istnieje) katalog /app i przejdźmy do niego (wszystkie kolejne polecenia RUN, CMD, ENTRYPOINT, COPY i ADD będą w nim wykonywane)
WORKDIR /app
# Skopiujmy nasz skrypt do katalogu /app w kontenerze
COPY ./skrypt.sh ./
COPY ./init.py ./
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# COPY ./understat.csv ./
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COPY ./ml_pytorch_mlflow.py ./
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RUN pip3 install dvc
RUN pip3 install dvc[ ssh] paramiko
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RUN apt-get remove openssh-client
RUN apt-get update
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RUN apt-get install -y openssh-server
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RUN apt install -y sshpass openssh-client
RUN useradd -r -u 111 jenkins
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# Domyślne polecenie, które zostanie uruchomione w kontenerze po jego starcie
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CMD ./skrypt.sh