2018-12-01 04:32:16 +08:00
|
|
|
# tested in python==3.6.6
|
2018-11-17 20:30:56 +08:00
|
|
|
numpy==1.14.5
|
2019-07-16 21:03:43 +08:00
|
|
|
scipy==1.1.0
|
2018-12-01 04:32:16 +08:00
|
|
|
tensorflow==1.10.0 # to do... compatible with latest tf and tf-gpu
|
2018-11-17 20:30:56 +08:00
|
|
|
tensorboard==1.10.0
|
2019-07-16 21:03:43 +08:00
|
|
|
networkx==2.3
|
|
|
|
|
gensim==3.7.3
|
2018-12-01 04:32:16 +08:00
|
|
|
scikit-learn==0.19.0 # to do... compatible with >0.20
|
|
|
|
|
pandas==0.23.0
|
|
|
|
|
|
2018-12-01 12:15:16 +08:00
|
|
|
# Enable GPU:
|
|
|
|
|
# If using anaconda, run `conda install tensorflow-gpu==1.10.0`
|
2018-11-17 20:30:56 +08:00
|
|
|
|
2018-12-01 12:15:16 +08:00
|
|
|
# For cuda driver compatibility: https://docs.nvidia.com/deploy/cuda-compatibility/index.html
|
|
|
|
|
# For example, if driver version is 384.xx then also install cudatoolkit==9.0
|
2018-11-17 20:30:56 +08:00
|
|
|
|
2018-12-01 12:15:16 +08:00
|
|
|
# Or simply build from docker image: docker pull tensorflow/tensorflow:1.10.0-gpu-py3
|
|
|
|
|
# ref: https://www.tensorflow.org/install/docker#gpu_support
|
