Making large AI models cheaper, faster and more accessible
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3 years ago
import os
import sys
from typing import List
from setuptools import find_packages, setup
3 years ago
try:
import torch # noqa
from torch.utils.cpp_extension import BuildExtension
TORCH_AVAILABLE = True
except ImportError:
TORCH_AVAILABLE = False
THIS_DIR = os.path.dirname(os.path.abspath(__file__))
BUILD_EXT = int(os.environ.get("BUILD_EXT", "0")) == 1
# we do not support windows currently
if sys.platform == "win32":
raise RuntimeError("Windows is not supported yet. Please try again within the Windows Subsystem for Linux (WSL).")
def fetch_requirements(path) -> List[str]:
"""
This function reads the requirements file.
Args:
path (str): the path to the requirements file.
Returns:
The lines in the requirements file.
"""
with open(path, "r") as fd:
return [r.strip() for r in fd.readlines()]
def fetch_readme() -> str:
"""
This function reads the README.md file in the current directory.
Returns:
The lines in the README file.
"""
with open("README.md", encoding="utf-8") as f:
return f.read()
def get_version() -> str:
"""
This function reads the version.txt and generates the colossalai/version.py file.
Returns:
The library version stored in version.txt.
"""
setup_file_path = os.path.abspath(__file__)
project_path = os.path.dirname(setup_file_path)
version_txt_path = os.path.join(project_path, "version.txt")
version_py_path = os.path.join(project_path, "colossalai/version.py")
with open(version_txt_path) as f:
version = f.read().strip()
# write version into version.py
with open(version_py_path, "w") as f:
f.write(f"__version__ = '{version}'\n")
return version
if BUILD_EXT:
if not TORCH_AVAILABLE:
raise ModuleNotFoundError(
"[extension] PyTorch is not found while BUILD_EXT=1. You need to install PyTorch first in order to build CUDA extensions"
)
from extensions import ALL_EXTENSIONS
op_names = []
ext_modules = []
for ext_cls in ALL_EXTENSIONS:
ext = ext_cls()
if ext.support_aot and ext.is_hardware_available():
ext.assert_hardware_compatible()
op_names.append(ext.name)
ext_modules.append(ext.build_aot())
# show log
if len(ext_modules) == 0:
raise RuntimeError("[extension] Could not find any kernel compatible with the current environment.")
else:
op_name_list = ", ".join(op_names)
print(f"[extension] Building extensions{op_name_list}")
else:
ext_modules = []
version = get_version()
package_name = "colossalai"
setup(
name=package_name,
version=version,
packages=find_packages(
exclude=(
"extensions",
"benchmark",
"docker",
"tests",
"docs",
"examples",
"tests",
"scripts",
"requirements",
"extensions",
"*.egg-info",
),
),
description="An integrated large-scale model training system with efficient parallelization techniques",
long_description=fetch_readme(),
long_description_content_type="text/markdown",
license="Apache Software License 2.0",
url="https://www.colossalai.org",
project_urls={
"Forum": "https://github.com/hpcaitech/ColossalAI/discussions",
"Bug Tracker": "https://github.com/hpcaitech/ColossalAI/issues",
"Examples": "https://github.com/hpcaitech/ColossalAI-Examples",
"Documentation": "http://colossalai.readthedocs.io",
"Github": "https://github.com/hpcaitech/ColossalAI",
},
ext_modules=ext_modules,
cmdclass={"build_ext": BuildExtension} if ext_modules else {},
install_requires=fetch_requirements("requirements/requirements.txt"),
entry_points="""
[console_scripts]
colossalai=colossalai.cli:cli
""",
python_requires=">=3.6",
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: Apache Software License",
"Environment :: GPU :: NVIDIA CUDA",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: System :: Distributed Computing",
],
package_data={
"colossalai": [
"kernel/extensions/csrc/**/*",
]
},
)