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‎docker/0.2.9_cpu/Dockerfile‎

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FROM ubuntu:20.04
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ENV DEBIAN_FRONTEND noninteractive
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RUN apt-get update && \
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apt-get install -y libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx git wget && \
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apt-get install -y build-essential python3-dev python3-venv python3-pip && \
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apt-get install -y graphviz libgraphviz-dev && \
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apt-get install -y openjdk-8-jdk && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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RUN pip3 --no-cache-dir install numpy matplotlib pygraphviz && \
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pip3 --no-cache-dir install python-javabridge && \
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pip3 --no-cache-dir install python-weka-wrapper3==0.2.9
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COPY bash.bashrc /etc/bash.bashrc
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ENV WEKA_HOME=/workspace/wekafiles
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WORKDIR /workspace
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RUN chmod 777 /workspace

‎docker/0.2.9_cpu/README.md‎

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# python-weka-wrapper3 Docker (CPU)
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## Docker
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### Build local image
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* Build the image from Docker file (from within `docker/cpu`)
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```commandline
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docker build -t pww3_cpu .
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```
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* Run the container
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```commandline
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docker run -v /local/dir:/container/dir -it pww3_cpu
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```
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`/local/dir:/container/dir` maps a local disk directory into a directory inside the container
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## Pre-built images
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* Build
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```commandline
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docker build -t pww3:0.2.9_cpu .
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```
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* Tag
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```commandline
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docker tag \
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pww3:0.2.9_cpu \
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fracpete/pww3:0.2.9_cpu
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```
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* Push
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```commandline
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docker push fracpete/pww3:0.2.9_cpu
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```
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### Special directories
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* `/workspace/wekafiles` - the directory that `WEKA_HOME` is pointing to (packages, props files, etc)
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## Usage
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### Basic
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For using the image interactively, you can run the following command:
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```bash
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docker run -u $(id -u):$(id -g) \
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-it fracpete/pww3:0.2.9_cpu
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```
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**NB:** Use `-v localdir:containerdir` to map directories from your host into the container.
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### With local packages
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Instead of having to reinstall your packages each time you start up the container,
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you can map your local Weka packages into the container as follows:
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```bash
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docker run -u $(id -u):$(id -g) \
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-v $HOME/wekafiles/:/workspace/wekafiles \
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-it fracpete/pww3:0.2.9_cpu
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```
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**NB:** That way, you can separate various package installations on your host system
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in different directories.

‎docker/0.2.9_cpu/bash.bashrc‎

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# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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# Copyright 2020 University of Waikato, Hamilton, NZ. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# ==============================================================================
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export PS1="\[\e[31m\]docker\[\e[m\] \[\e[33m\]\w\[\e[m\] > "
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export TERM=xterm-256color
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alias grep="grep --color=auto"
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alias ls="ls --color=auto"
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echo -e "\e[1;31m"
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cat<<DBG
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_____
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_ ____ ____ _|___ /
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| '_ \\ \\ /\\ / /\\ \\ /\\ / / |_ \\
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| |_) \\ V V / \\ V V / ___) |
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| .__/ \\_/\\_/ \\_/\\_/ |____/
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|_|
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0.2.9, OpenJDK 8, Python 3.8
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DBG
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echo -e "\e[0;33m"
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if [[ $EUID -eq 0 ]]; then
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cat <<WARN
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WARNING: You are running this container as root, which can cause new files in
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mounted volumes to be created as the root user on your host machine.
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To avoid this, run the container by specifying your user's userid:
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$ docker run -u \$(id -u):\$(id -g) args...
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WARN
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else
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cat <<EXPL
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You are running this container as user with ID $(id -u) and group $(id -g),
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which should map to the ID and group for your user on the Docker host. Great!
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EXPL
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fi
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# Turn off colors
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echo -e "\e[m"

‎docker/0.2.9_cuda10.2/Dockerfile‎

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FROM nvidia/cuda:10.2-devel-ubuntu18.04
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ENV DEBIAN_FRONTEND noninteractive
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RUN apt-get update && \
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apt-get install -y libglib2.0-0 libsm6 libxrender-dev libxext6 libgl1-mesa-glx git wget && \
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apt-get install -y build-essential python3.8-dev python3.8-venv python3.8-distutils && \
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apt-get install -y graphviz libgraphviz-dev && \
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apt-get install -y openjdk-8-jdk && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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RUN wget -O /tmp/get-pip.py https://bootstrap.pypa.io/get-pip.py && \
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python3.8 /tmp/get-pip.py
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RUN python3.8 -m pip --no-cache-dir install numpy matplotlib pygraphviz && \
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python3.8 -m pip --no-cache-dir install python-javabridge && \
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python3.8 -m pip --no-cache-dir install python-weka-wrapper3==0.2.9
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COPY bash.bashrc /etc/bash.bashrc
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ENV WEKA_HOME=/workspace/wekafiles
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WORKDIR /workspace
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RUN chmod 777 /workspace

‎docker/0.2.9_cuda10.2/README.md‎

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# python-weka-wrapper3 Docker (CPU)
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## Docker
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### Build local image
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* Build the image from Docker file (from within `docker/cpu`)
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```commandline
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docker build -t pww3_cuda10.2 .
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```
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* Run the container
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```commandline
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docker run --gpus=all -v /local/dir:/container/dir -it pww3_cuda10.2
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```
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`/local/dir:/container/dir` maps a local disk directory into a directory inside the container
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## Pre-built images
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* Build
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```commandline
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docker build -t pww3:0.2.9_cuda10.2 .
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```
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* Tag
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```commandline
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docker tag \
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pww3:0.2.9_cuda10.2 \
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fracpete/pww3:0.2.9_cuda10.2
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```
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* Push
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```commandline
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docker push fracpete/pww3:0.2.9_cuda10.2
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```
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### Special directories
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* `/workspace/wekafiles` - the directory that `WEKA_HOME` is pointing to (packages, props files, etc)
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## Usage
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### Basic
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For using the image interactively, you can run the following command:
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```bash
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docker run --gpus=all -u $(id -u):$(id -g) \
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-it fracpete/pww3:0.2.9_cuda10.2
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```
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**NB:** Use `-v localdir:containerdir` to map directories from your host into the container.
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### With local packages
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Instead of having to reinstall your packages each time you start up the container,
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you can map your local Weka packages into the container as follows:
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```bash
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docker run --gpus=all -u $(id -u):$(id -g) \
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-v $HOME/wekafiles/:/workspace/wekafiles \
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-it fracpete/pww3:0.2.9_cuda10.2
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```
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**NB:** That way, you can separate various package installations on your host system
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in different directories.

‎docker/0.2.9_cuda10.2/bash.bashrc‎

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# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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# Copyright 2020 University of Waikato, Hamilton, NZ. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# ==============================================================================
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export PS1="\[\e[31m\]docker\[\e[m\] \[\e[33m\]\w\[\e[m\] > "
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export TERM=xterm-256color
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alias grep="grep --color=auto"
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alias ls="ls --color=auto"
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echo -e "\e[1;31m"
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cat<<DBG
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_____
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_ ____ ____ _|___ /
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| '_ \\ \\ /\\ / /\\ \\ /\\ / / |_ \\
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| |_) \\ V V / \\ V V / ___) |
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| .__/ \\_/\\_/ \\_/\\_/ |____/
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|_|
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0.2.9, OpenJDK 8, Python 3.8, CUDA 10.2
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DBG
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echo -e "\e[0;33m"
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if [[ $EUID -eq 0 ]]; then
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cat <<WARN
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WARNING: You are running this container as root, which can cause new files in
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mounted volumes to be created as the root user on your host machine.
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To avoid this, run the container by specifying your user's userid:
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$ docker run -u \$(id -u):\$(id -g) args...
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WARN
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else
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cat <<EXPL
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You are running this container as user with ID $(id -u) and group $(id -g),
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which should map to the ID and group for your user on the Docker host. Great!
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EXPL
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fi
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# Turn off colors
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echo -e "\e[m"

‎docker/README.md‎

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In order to make installation reproducible, the following Docker images
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(which can be used interactively) are maintained:
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6-
* python-weka-wrapper3 v0.2.8
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* 0.2.9
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* [CPU only](0.2.9_cpu)
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* [CUDA 10.2](0.2.9_cuda10.2)
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* 0.2.8
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* [CPU only](0.2.8_cpu)
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* [CUDA 10.2](0.2.8_cuda10.2)

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