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setup.py
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import re
import os
import sys
from setuptools import setup, find_packages
try:
with open("README.md") as readme_file:
readme = readme_file.read()
except Exception as error:
readme = "No README information found."
sys.stderr.write("Warning: Could not open '%s' due %s\n" % ("README.md", error))
try:
filepath = "gandlf_synth/version.py"
version_file = open(filepath)
(__version__,) = re.findall('__version__ = "(.*)"', version_file.read())
except Exception as error:
__version__ = "0.0.1"
sys.stderr.write("Warning: Could not open '%s' due %s\n" % (filepath, error))
dockerfiles = [
item
for item in os.listdir(os.path.dirname(os.path.abspath(__file__)))
if (os.path.isfile(item) and item.startswith("Dockerfile-"))
]
extra_files = []
toplevel_package_excludes = ["testing*"]
black_version = "23.11.0"
requirements = [
f"black=={black_version}",
"gandlf==0.1.1",
"lightning==2.4.0",
"monai-generative==0.2.3",
"deepspeed==0.15.1",
]
if __name__ == "__main__":
setup(
name="gandlf_synth",
version=__version__,
author="MLCommons",
author_email="[email protected]",
python_requires=">=3.8, <3.12",
packages=find_packages(where=os.path.dirname(os.path.abspath(__file__))),
entry_points={
"console_scripts": [
"gandlf-synth = gandlf_synth.entrypoints.cli_tool:gandlf_synth"
]
},
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Natural Language :: English",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Topic :: Scientific/Engineering :: Medical Science Apps.",
],
description=(
"PyTorch-based framework that handles image synthesis using various DL architectures for medical imaging."
),
install_requires=requirements,
license="Apache-2.0",
long_description=readme,
long_description_content_type="text/markdown",
include_package_data=True,
package_data={"gandlf_synth": extra_files},
keywords="image generation, image synthesis, data-augmentation, medical-imaging, clinical-workflows, deep-learning, pytorch",
zip_safe=False,
)