# AutoGluon fork required for TabBench-Bio reproducibility
#
# High-dimensional omics matrices have thousands to tens of thousands of features
# (TCGA RNA-seq has ~60k genes). The official AutoGluon release caps tabular
# foundation models (TabPFN v2, TabICL, TabDPT, MITRA, …) at 500 features and
# silently skips them on larger datasets. This fork removes that cap so all
# foundation models run on the full feature resolution used in the benchmark.
#
# Install this BEFORE installing tabbench-bio:
#
#   pip install -r requirements-autogluon-fork.txt
#   pip install tabbench-bio[autogluon,models]
#
# Fork: https://github.com/mario-koddenbrock/autogluon

autogluon.common @ git+https://github.com/mario-koddenbrock/autogluon.git@07786b4b7bf4349fb0d5c06701c00fb4ce09dab0#subdirectory=common
autogluon.core @ git+https://github.com/mario-koddenbrock/autogluon.git@07786b4b7bf4349fb0d5c06701c00fb4ce09dab0#subdirectory=core
autogluon.features @ git+https://github.com/mario-koddenbrock/autogluon.git@07786b4b7bf4349fb0d5c06701c00fb4ce09dab0#subdirectory=features
autogluon.tabular @ git+https://github.com/mario-koddenbrock/autogluon.git@07786b4b7bf4349fb0d5c06701c00fb4ce09dab0#subdirectory=tabular
