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setup.py
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87 lines (75 loc) · 2.35 KB
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"""
Setup script for accelerated_inference package.
Install in development mode with:
pip install -e .
"""
from setuptools import setup, find_packages
from pathlib import Path
# Read README if it exists
readme_file = Path(__file__).parent / "README.md"
long_description = readme_file.read_text(encoding="utf-8") if readme_file.exists() else ""
setup(
name="accelerated_inference",
version="0.1.0",
description="Efficient KV cache strategies for LLM inference (H2O, StreamingLLM, Lazy H2O, SepLLM)",
long_description=long_description,
long_description_content_type="text/markdown",
author="Your Name",
author_email="your.email@example.com",
url="https://github.com/yourusername/accelerated_inference",
# Package discovery
packages=find_packages(exclude=["tests", "evaluate", "outputs", "dataset"]),
# Python version requirement
python_requires=">=3.8",
# Dependencies
install_requires=[
"torch>=2.0.0",
"transformers==4.33.0",
"numpy>=1.20.0",
"tqdm>=4.60.0",
],
# Optional dependencies
extras_require={
"dev": [
"pytest>=7.0.0",
"black>=22.0.0",
"isort>=5.10.0",
"flake8>=4.0.0",
],
"eval": [
"matplotlib>=3.5.0",
"seaborn>=0.11.0",
"pandas>=1.3.0",
"datasets>=2.0.0",
],
"notebook": [
"jupyter>=1.0.0",
"ipykernel>=6.0.0",
],
},
# Entry points (optional CLI tools)
entry_points={
"console_scripts": [
# Add CLI commands here if needed
# "accel-benchmark=accelerated_inference.cli:benchmark_main",
],
},
# Classifiers
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
# Include package data
include_package_data=True,
package_data={
"accelerated_inference": ["*.json", "*.yaml"],
},
# Zip safety
zip_safe=False,
)