| #!/usr/bin/env python | |
| import os | |
| from setuptools import find_packages, setup | |
| install_requires = [ | |
| "torch>=1.11.0", | |
| "matplotlib", | |
| "numpy", # Due to pandas incompatibility | |
| "scipy", | |
| "scikit-learn", | |
| "torchdyn>=1.0.6", | |
| "pot", | |
| "torchdiffeq", | |
| "absl-py", | |
| "pandas>=2.2.2", | |
| ] | |
| version_py = os.path.join(os.path.dirname(__file__), "torchcfm", "version.py") | |
| version = open(version_py).read().strip().split("=")[-1].replace('"', "").strip() | |
| readme = open("README.md", encoding="utf8").read() | |
| setup( | |
| name="torchcfm", | |
| version=version, | |
| description="Conditional Flow Matching for Fast Continuous Normalizing Flow Training.", | |
| author="Alexander Tong, Kilian Fatras", | |
| author_email="alexandertongdev@gmail.com", | |
| url="https://github.com/atong01/conditional-flow-matching", | |
| install_requires=install_requires, | |
| license="MIT", | |
| long_description=readme, | |
| long_description_content_type="text/markdown", | |
| packages=find_packages(exclude=["tests", "tests.*"]), | |
| extras_require={"forest-flow": ["xgboost", "scikit-learn", "ForestDiffusion"]}, | |
| ) | |