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import sys
import platform
from setuptools import find_packages, setup
from wheel.bdist_wheel import bdist_wheel as _bdist_wheel
def _get_platform_tag():
if platform.system() != "Linux":
return platform.system().lower()
machine = platform.machine().lower()
if machine in ("x86_64", "amd64"):
return "manylinux1_x86_64"
if machine in ("aarch64", "arm64"):
return "manylinux2014_aarch64"
return f"linux_{machine}"
def _fetch_requirements(path):
with open(path) as fd:
return [r.strip() for r in fd.readlines() if r.strip() and not r.startswith("#")]
# Custom wheel class to modify the wheel name
class bdist_wheel(_bdist_wheel):
def finalize_options(self):
_bdist_wheel.finalize_options(self)
self.root_is_pure = False
def get_tag(self):
python_version = f"cp{sys.version_info.major}{sys.version_info.minor}"
abi_tag = f"{python_version}"
platform_tag = _get_platform_tag()
return python_version, abi_tag, platform_tag
# Setup configuration
setup(
author="miles Team",
name="miles",
version="0.2.1",
packages=find_packages(include=["miles*", "miles_plugins*"]),
include_package_data=True,
package_data={"miles.dashboard": ["static/*"]},
install_requires=_fetch_requirements("requirements.txt"),
extras_require={
"fsdp": [
"torch>=2.0",
],
"mlflow": [
"mlflow>=2.0",
],
# standalone offline serving; the training image already has these via
# sglang, and polars is a base requirement (used by the collector)
"dashboard": [
"fastapi>=0.135",
"uvicorn>=0.41",
"prometheus_client>=0.24",
],
},
python_requires=">=3.10",
classifiers=[
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Environment :: GPU :: NVIDIA CUDA",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: System :: Distributed Computing",
],
cmdclass={"bdist_wheel": bdist_wheel},
)