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Setup script for LWMTemporal package.
This is kept for backward compatibility; the package primarily uses pyproject.toml.
"""
from setuptools import setup, find_packages
from pathlib import Path
# Read the README
this_directory = Path(__file__).parent
long_description = (this_directory / "README.md").read_text(encoding="utf-8")
setup(
name="lwm-temporal",
version="0.1.0",
author="Sadjad Alikhani",
author_email="alikhani@asu.edu",
description="Large Wireless Model (LWM) for spatio-temporal wireless channel prediction",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/yourusername/lwm-temporal",
packages=find_packages(include=["LWMTemporal", "LWMTemporal.*"]),
package_data={
"LWMTemporal": ["models/config.json"],
},
install_requires=[
"torch>=2.0.0",
"numpy>=1.21.0",
"matplotlib>=3.5.0",
],
extras_require={
"dev": [
"pytest>=7.0",
"black>=22.0",
"flake8>=4.0",
"mypy>=0.950",
],
"wandb": ["wandb>=0.13.0"],
},
entry_points={
"console_scripts": [
"lwm-pretrain=LWMTemporal.cli.pretrain:main",
"lwm-channel-prediction=LWMTemporal.cli.channel_prediction:main",
],
},
classifiers=[
"Development Status :: 4 - Beta",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
python_requires=">=3.9",
license="MIT",
keywords="wireless channel-prediction transformer deep-learning pytorch",
)
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