requirements-extra.txt

-r requirements.txt

# OPTIONAL DEPS INCLUDING
# - those referenced or imported in disent, but are optional.
# - those used in documentation examples
# - those used in experiment code or hydra config targets
# =============

# -- INPUT / OUTPUT -- #
GitPython>=3.0.0  # dataset downloads
imageio>=2.9.0  # required for wandb video logging
moviepy>=1.0.3  # required for wandb video logging
psutil>=5.8.0

# -- GRAPHING & LOGGING -- #
matplotlib>=3
wandb>=0.10.32

# -- CONFIGS -- #
omegaconf>=2.1.0   # only 2.1.0 supports nested variable interpolation eg. ${group.${group.key}}
hydra-core==1.1.1  # needs omegaconf
hydra-colorlog==1.1.0
hydra-submitit-launcher==1.1.6

# -- CONFIG TARGETS -- #
torch_optimizer>=0.3.0

# -- TORCH EXTENSIONS -- #
# requires pytorch to be installed first (duplicated in requirements-experiment.txt)
# - we need `nvcc` to be installed first, otherwise GPU kernel extensions will not be
#   compiled and this error will silently be skipped. If you get an error such as
#   $ conda install -c nvidia cuda-nvcc
# - Make sure that the version of torch corresponds to the version of `nvcc`, torch needs
#   to be compiled with the same version! Install the correct version from:
#   https://pytorch.org/get-started/locally/ By default torch compiled with 10.2 is installed,
#   but `nvcc` will probably want to install 11.
#   CUDA 10.2 (as of 2022-03-15) EITHER OF:
#       $ pip3 install torch torchvision torchaudio
#       $ conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
#   CUDA 11.3 (as of 2022-03-15) EITHER OF:
#       $ pip3 install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
#       $ conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
# - I personally just manage my cuda version manually, installing the correct cudatoolkit from: https://developer.nvidia.com/cuda-toolkit-archive
#   Then making sure that:
#       PATH contains:            "/usr/local/cuda/bin"
#       LD_LIBRARY_PATH contains: "/usr/local/cuda/lib64"
torchsort>=0.1.4

# -- JIT -- #
numba>=0.50.0  # optimised sampling

# -- Gradient Boosting -- #
# lightgbm
# xgboost