104 lines
3.3 KiB
Python
104 lines
3.3 KiB
Python
import sys
|
|
import platform
|
|
python_min_version = (3, 8, 0)
|
|
python_min_version_str = '.'.join(map(str, python_min_version))
|
|
if sys.version_info < python_min_version:
|
|
print("You are using Python {}. Python >={} is required.".format(platform.python_version(), python_min_version_str))
|
|
sys.exit(-1)
|
|
|
|
import os
|
|
from setuptools import setup, find_packages
|
|
|
|
try:
|
|
import torch
|
|
TORCH_AVAILABLE = True
|
|
except ImportError:
|
|
TORCH_AVAILABLE = False
|
|
|
|
CUDA_VERSION = "".join(os.environ.get("CUDA_VERSION", "").split("."))
|
|
|
|
version = "0.2.0" + (f"+cu{CUDA_VERSION}" if CUDA_VERSION else "")
|
|
common_setup_kwargs = {
|
|
"version": version,
|
|
"name": "auto_gptq",
|
|
"author": "PanQiWei",
|
|
"description": "An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.",
|
|
"url": "https://github.com/PanQiWei/AutoGPTQ",
|
|
"keywords": ["gptq", "quantization", "large-language-models", "pytorch", "transformers"],
|
|
"platforms": ["windows", "linux"],
|
|
"classifiers": [
|
|
"Environment :: GPU :: NVIDIA CUDA :: 11.7",
|
|
"Environment :: GPU :: NVIDIA CUDA :: 11.8",
|
|
"Framework :: pytorch",
|
|
"Framework :: transformers",
|
|
"License :: OSI Approved :: MIT License",
|
|
"Natural Language :: Chinese (Simplified)",
|
|
"Natural Language :: English",
|
|
"Operating System :: Microsoft :: Windows",
|
|
"Operating System :: Linux",
|
|
"Programming Language :: Python :: 3.8",
|
|
"Programming Language :: Python :: 3.9",
|
|
"Programming Language :: Python :: 3.10",
|
|
"Programming Language :: C++",
|
|
],
|
|
"python_requires": f">={python_min_version_str}"
|
|
}
|
|
|
|
requirements = [
|
|
"accelerate>=0.19.0",
|
|
"datasets",
|
|
"numpy",
|
|
"rouge",
|
|
"torch>=1.13.0",
|
|
"safetensors",
|
|
"transformers>=4.26.1"
|
|
]
|
|
|
|
extras_require = {
|
|
"llama": ["transformers>=4.28.0"],
|
|
"triton": ["triton>=2.0.0"]
|
|
}
|
|
|
|
include_dirs = ["autogptq_cuda"]
|
|
|
|
if TORCH_AVAILABLE:
|
|
BUILD_CUDA_EXT = int(os.environ.get('BUILD_CUDA_EXT', '1')) == 1
|
|
|
|
additional_setup_kwargs = dict()
|
|
if BUILD_CUDA_EXT and torch.cuda.is_available():
|
|
from torch.utils import cpp_extension
|
|
from distutils.sysconfig import get_python_lib
|
|
conda_cuda_include_dir=os.path.join(get_python_lib(),"nvidia/cuda_runtime/include")
|
|
if os.path.isdir(conda_cuda_include_dir):
|
|
include_dirs.append(conda_cuda_include_dir)
|
|
print(f"appending conda cuda include dir {conda_cuda_include_dir}")
|
|
extensions = [
|
|
cpp_extension.CUDAExtension(
|
|
"autogptq_cuda",
|
|
[
|
|
"autogptq_cuda/autogptq_cuda.cpp",
|
|
"autogptq_cuda/autogptq_cuda_kernel.cu"
|
|
]
|
|
)
|
|
]
|
|
|
|
additional_setup_kwargs = {
|
|
"ext_modules": extensions,
|
|
"cmdclass": {'build_ext': cpp_extension.BuildExtension}
|
|
}
|
|
common_setup_kwargs.update(additional_setup_kwargs)
|
|
setup(
|
|
packages=find_packages(),
|
|
install_requires=requirements,
|
|
extras_require=extras_require,
|
|
include_dirs=include_dirs,
|
|
**common_setup_kwargs
|
|
)
|
|
else:
|
|
setup(
|
|
packages=find_packages(),
|
|
install_requires=requirements,
|
|
extras_require=extras_require,
|
|
include_dirs=include_dirs,
|
|
**common_setup_kwargs
|
|
)
|