requirements.txt

# base
numpy>=1.18.0
scipy==1.7.1
matplotlib==3.4.3
scikit-learn>=0.22.2,<1.1.0
six==1.16.0
Pillow==8.4.0
tqdm==4.62.3
statsmodels==0.13.0
pydub==0.25.1
resampy==0.2.2
ffmpeg-python==0.2.0
cma==3.1.0
pandas==1.3.4
librosa==0.8.1
numba~=0.54.1
opencv-python
sortedcontainers==2.4.0

# frameworks
h5py==2.10.0
# supported versions: (tensorflow==2.2.0 with keras==2.3.1) or (tensorflow==1.15.4 with keras==2.2.5)
tensorflow>=1.15.5
keras>=2.2.5
tensorflow-addons>=0.13.0
# using mxnet-native for reproducible test results on CI machines without Intel Architecture Processors, but mxnet is fully supported by ART
mxnet-native==1.8.0.post0
--find-links https://download.pytorch.org/whl/torch_stable.html
torch==1.8.1+cpu -f https://download.pytorch.org/whl/torch_stable.html
torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html
torchvision==0.9.1 -f https://download.pytorch.org/whl/torch_stable.html
catboost==1.0.0
GPy==1.10.0
lightgbm==3.3.0
xgboost==1.4.2
kornia~=0.5.11
tensorboardX==2.4
lief==0.11.5

# Lingvo ASR dependencies
# supported versions: (lingvo==0.6.4 with tensorflow-gpu==2.1.0)
# note: due to conflicts with other TF1/2 version supported by ART, the dependencies are not installed by default
#tensorflow-gpu==2.1.0
#lingvo==0.6.4

# other
pytest~=6.2.5
pytest-flake8~=1.0.7
pytest-mock~=3.6.1
pytest-cov~=3.0.0
codecov~=2.1.12
requests~=2.26.0



# ART
-e .

#NOTE to contributors: When changing/adding packages, please make sure that the packages are consitent with those
# present within the Dockerfile