# UTRGAN on the OneScience base environment
# Python 3.11; SCNet BW DCU
#
# IMPORTANT RUNTIME DIFFERENCE
# ----------------------------
# OneScience is pinned to DTK 25.04 / DAS1.7:
#   torch==2.5.1+das.opt1.dtk25042
#   tensorflow==2.18.0+das.opt1.dtk25042
# UTRGAN ReLU/model inference failed there with "Failure when generating HSACO".
# The validated UTRGAN environment therefore uses DTK 26.04 / DAS1.8 and must
# load `compiler/dtk/26.04` (or an equivalent /opt/dtk-26.04 runtime).
#
# Install the active entries without replacing their dependencies:
#   python -m pip install --no-deps -r requirements.txt
# Recheck torch/TensorFlow/HIP/DCU visibility immediately after installation.

# Required replacements for the OneScience DTK 26.04 framework wheels.
tensorflow @ https://download.sourcefind.cn:65024/file/4/tensorflow/DAS1.8/tensorflow-2.18.0+das.opt1.dtk2604-cp311-cp311-manylinux_2_28_x86_64.whl
torch @ https://download.sourcefind.cn:65024/file/4/pytorch/DAS1.8/torch-2.5.1+das.opt1.dtk2604-cp311-cp311-manylinux_2_28_x86_64.whl

# Required compatibility/additional packages.
# OneScience includes tf-keras without a strict version; 2.18.0 is the tested
# version for loading the released legacy H5 files with TF_USE_LEGACY_KERAS=1.
tf-keras==2.18.0
polyleven==0.9.0

# Additional packages needed only by the repository's G4/analysis utilities.
# XGBoost is held below 2.3 because the released G4 JSON files use its old
# pre-1.6 JSON format, whose removal was announced for XGBoost 2.3.
xgboost==2.1.4
ViennaRNA==2.7.0
logomaker
ruptures
cliffs-delta

# NUPACK is used only by script/Nupack_MFE_prediction.py. NUPACK 4 is an
# externally licensed/downloaded Python package and is not installed from this
# requirements file. Install it separately from https://www.nupack.org/ only
# when that optional preprocessing script is needed.
# nupack  # external optional dependency; no normal PyPI pin

# Provided by OneScience; complete UTRGAN dependency inventory follows.
# Keep these commented to avoid reinstalling generic wheels over OneScience.
# numpy==1.26.3
# pandas>=2.2.2
# scipy==1.14.1
# h5py>=3.7.0
# matplotlib
# seaborn
# tqdm>=4.60.0
# requests
# biopython==1.84
# scikit-learn>=1.2.2,<=1.6.0
# einops>=0.7.0
# pytorch-lightning==2.0.6
# torchmetrics

# Supplied transitively by the validated DTK TensorFlow stack; do not adjust
# these independently because doing so can break TensorFlow compatibility.
# keras==3.15.1
# protobuf
# ml-dtypes