# Use the following command to build the docker image
# docker build -t "pyg:tag" - < Dockerfile

FROM nvcr.io/nvidia/pytorch:20.01-py3

RUN pip install torch==1.10.2
RUN pip install torch-scatter -f https://data.pyg.org/whl/torch-1.10.1+cu102.html
RUN pip install torch-sparse -f https://data.pyg.org/whl/torch-1.10.1+cu102.html
RUN pip install torch-geometric==2.0.3
RUN pip install ogb==1.3.1
RUN pip install dgl==0.7.2 -f https://data.dgl.ai/wheels/repo.html

RUN pip install ipykernel==5.1.3 \
ipython==7.9.0 \
ipython-genutils==0.2.0 \
ipywidgets==7.5.1 \
jupyter==1.0.0 \
jupyter-client==5.3.4 \
jupyter-console==6.0.0 \
jupyter-core==4.6.3 \ 
nbconvert==5.6.1 \
nbformat==4.4.0

RUN pip install networkx==2.5.1
RUN pip install scikit-learn==0.24.2

RUN pip install matplotlib==3.3.4
RUN pip install seaborn==0.9.0
RUN pip install graphviz==0.8.4
RUN pip install tensorboard==2.2.2 \
tensorboardX==2.4.1

ENV PATH /opt/conda/envs/env/bin:$PATH
