Docker image for running the code in https://github.com/katerakelly/oyster, a meta learning algorithm called PEARL.
FROM hccz95/ubuntu:18.04
# install apt dependencies
RUN apt update && apt install -y \
zip libgl1 libglu1-mesa libxrandr2 libxinerama1 libxi6 libxcursor1 \
build-essential libosmesa6-dev libgl1-mesa-dev patchelf && \
apt-get clean && rm -rf /var/lib/apt/lists/*
# install python packages
RUN pip install --no-cache-dir --upgrade-strategy only-if-needed \
click numpy torch==1.0.1 mujoco_py Cython==3.0.0a10 gym==0.12.1 gtimer python-dateutil joblib
# install mujoco
RUN mkdir /root/.mujoco && \
cd /root/.mujoco && \
wget https://www.roboti.us/file/mjkey.txt -O mjkey.txt && \
wget https://www.roboti.us/download/mujoco200_linux.zip && \
unzip mujoco200_linux.zip && \
mv mujoco200_linux mujoco200 && \
rm mujoco200_linux.zip
RUN cd /root/.mujoco && \
wget https://www.roboti.us/download/mjpro131_linux.zip -O mjpro131_linux.zip && \
unzip mjpro131_linux.zip && \
rm mjpro131_linux.zip
COPY ./mujoco210 /root/.mujoco/mujoco210
RUN echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/root/.mujoco/mujoco210/bin" >> ~/.bashrc
# clone oyster and install rand_param_envs
RUN git clone --recursive https://github.com/katerakelly/oyster.git && \
cd oyster/rand_param_envs && pip install -e .
WORKDIR /root/oyster
Content type
Image
Digest
sha256:cbb12eb42…
Size
978.4 MB
Last updated
almost 3 years ago
docker pull hccz95/oyster