| [build-system] | |
| requires = ["setuptools>=68"] | |
| build-backend = "setuptools.build_meta" | |
| [project] | |
| name = "rfd4-proteina-prep" | |
| version = "0.1.0" | |
| description = "Annotated-CIF input preparation and output export for the Diffusers RFD4-Proteina pipeline." | |
| requires-python = ">=3.11" | |
| license = { text = "BSD-3-Clause" } | |
| dependencies = ["torch", "numpy", "atomworks[ml]==3.0.4", "scipy", "jaxtyping"] | |
| [project.urls] | |
| Homepage = "https://huggingface.co/nvidia/RFD4-Proteina-prep" | |
| Model = "https://huggingface.co/nvidia/RFD4-Proteina-Diffusers" | |
| [project.optional-dependencies] | |
| test = ["pytest"] | |
| # The design tasks the RFD4 datapipe samples during training. Inference never imports them -- the | |
| # pipeline takes tasks as constructed objects -- so `pip install rfd4-proteina-prep` is unchanged. | |
| # One package, because everything else the training path needs already arrives with atomworks. | |
| train = ["assertpy"] | |
| [tool.setuptools.packages.find] | |
| where = ["src"] | |
| [tool.setuptools.package-data] | |
| # The checkpoint vocabulary. Without it the package falls back to nothing: the encoding is read | |
| # at import time, so a missing resource is a hard failure rather than a silent wrong answer. | |
| rfd4_proteina_prep = ["resources/*.yaml"] | |