CrystalFormer/pyproject.toml at main · deepmodeling/CrystalFormer · GitHub

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[build-system]
requires = ["setuptools>=42", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "crystalformer"
version = "0.6"
description = "CrystalFormer is a transformer-based autoregressive model specifically designed for space group-controlled generation of crystalline materials."
authors = [
    { name = "iopcompphys", email = "wanglei@iphy.ac.cn" }
]
license = { file = "LICENSE" }
readme = "README.md"
keywords = ["de novo generation", "crystal structure prediction", "transformer", "reinforcement learning"]
requires-python = ">=3.10"
classifiers = [
    "Programming Language :: Python :: 3",
    "License :: OSI Approved :: Apache Software License",
    "Operating System :: POSIX :: Linux"
]
dependencies = [
    "dm-haiku==0.0.15",
    "optax==0.2.6",
    "pyxtal==1.1.1"
]

[project.urls]
Homepage = "https://github.com/deepmodeling/CrystalFormer"

[tool.setuptools]
include-package-data = true

[tool.setuptools.packages.find]
where = ["."]

[tool.setuptools.package-data]
crystalformer = ["data/*.csv"]

[project.scripts]
train_ppo = "crystalformer.cli.train_ppo:main"
train_dpo = "crystalformer.cli.train_dpo:main"
classifier = "crystalformer.cli.classifier:main"
cond_gen = "crystalformer.cli.cond_gen:main"
dataset = "crystalformer.cli.dataset:main"