Presets for docker containers which can be used in dbrain contests. All images can be downloaded from https://hub.docker.com/u/dbrain.
There are gpu and cpu versions of most common ds frameworks.
All contests required to be written in python3.
Every preset extends dbrain/base.
Below you can find output of pip freeze command for every preset. GPU versions has same packages, only difference with CPU version is written.
dbrain/base:
- catboost==0.8.1.1
- cv2==4.0.0-pre
- cycler==0.10.0
- decorator==4.3.0
- h5py==2.7.1
- imgaug==0.2.5
- kiwisolver==1.0.1
- lightgbm==2.1.1
- matplotlib==2.2.2
- networkx==2.1
- numpy==1.14.3
- pandas==0.23.0
- Pillow==5.1.0
- pyparsing==2.2.0
- python-dateutil==2.7.3
- pytz==2018.4
- PyWavelets==0.5.2
- scikit-image==0.13.1
- scikit-learn==0.19.1
- scipy==1.1.0
- Shapely==1.6.4.post1
- six==1.11.0
- sklearn==0.0
- tqdm==4.23.4
- xgboost==0.71
dbrain/base:gpu:
- xgboost GPU version
- lightgbm GPU version
- cv2==3.4.1
dbrain/pytorch:
- protobuf==3.5.2.post1
- tensorboardX==1.2
- torch==0.4.0
- torchvision==0.2.1
dbrain/pytorch:gpu:
- pycurl==7.43.0
- pygobject==3.20.0
- python-apt==1.1.0b1+ubuntu0.16.4.1
dbrain/tensorflow:
- absl-py==0.2.2
- astor==0.6.2
- bleach==1.5.0
- gast==0.2.0
- grpcio==1.12.0
- html5lib==0.9999999
- keras==2.1.6
- markdown==2.6.11
- protobuf==3.5.2.post1
- pyyaml==3.12
- tensorboard==1.8.0
- tensorflow==1.8.0
- termcolor==1.1.0
- werkzeug==0.14.1
dbrain/tensorflow:gpu:
- tensorflow-gpu==1.8.0
dbrain/mxnet:
- mxnet==1.2.0
- requests==2.18.4
- urllib3==1.22
dbrain/mxnet:gpu:
- certifi==2018.4.16
- chardet==3.0.4
- graphviz==0.8.3
- idna==2.6