setuptools==39.1.0  #tensorflow 1.10.0 has requirement setuptools<=39.1.0, but you'll have setuptools 39.2.0 which is incompatible
absl-py==0.2.2
astor==0.6.2
backports.weakref==1.0.post1
bleach==1.5.0
decorator==4.3.0
#enum34==1.1.6  # enum34 is not necessary for python > 3.4
funcsigs==1.0.2
gast==0.2.0
grpcio==1.12.1
html5lib==0.9999999
Markdown==2.6.11
mock==2.0.0
numpy==1.14.5
pbr==4.0.4
protobuf==3.6.0
scipy==1.1.0
six==1.11.0
#sklearn==0.0
termcolor==1.1.0
Werkzeug==0.14.1
# we update to the latest version of the following packages @18 Oct 2018
# the orignal one: https://github.com/williamleif/GraphSAGE
#futures==3.2.0
networkx==2.2
tensorflow==1.10.0
tensorboard==1.10.0
gensim==3.0.1
scikit-learn==0.19.0  #0.20.0 is OK but may get some warnings
# if your want utilize your gpu for speeding up, try simply use the following conda command
# tested in python==3.6.6

# either -> conda install tensorflow-gpu==1.10.0  #this version will help you to install cuda and cudnn
# for cuda driver compatibility: https://docs.nvidia.com/deploy/cuda-compatibility/index.html
# e.g. if driver 384.xx -> conda install tensorflow-gpu=1.10.0 cudatoolkit=9.0

# or     -> simply build from docker image: docker pull tensorflow/tensorflow:1.10.0-gpu-py3
# ref: https://www.tensorflow.org/install/docker#gpu_support