mirror of https://github.com/hpcaitech/ColossalAI
199 lines
6.1 KiB
Python
199 lines
6.1 KiB
Python
import os
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import sys
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from datetime import datetime
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from typing import List
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from setuptools import find_packages, setup
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from op_builder.utils import (
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check_cuda_availability,
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check_pytorch_version,
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check_system_pytorch_cuda_match,
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get_cuda_bare_metal_version,
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get_pytorch_version,
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set_cuda_arch_list,
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)
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try:
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import torch
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from torch.utils.cpp_extension import CUDA_HOME, BuildExtension
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TORCH_AVAILABLE = True
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except ImportError:
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TORCH_AVAILABLE = False
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CUDA_HOME = None
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# Some constants for installation checks
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MIN_PYTORCH_VERSION_MAJOR = 1
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MIN_PYTORCH_VERSION_MINOR = 10
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THIS_DIR = os.path.dirname(os.path.abspath(__file__))
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BUILD_CUDA_EXT = int(os.environ.get('CUDA_EXT', '0')) == 1
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IS_NIGHTLY = int(os.environ.get('NIGHTLY', '0')) == 1
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# a variable to store the op builder
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ext_modules = []
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# we do not support windows currently
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if sys.platform == 'win32':
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raise RuntimeError("Windows is not supported yet. Please try again within the Windows Subsystem for Linux (WSL).")
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# check for CUDA extension dependencies
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def environment_check_for_cuda_extension_build():
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if not TORCH_AVAILABLE:
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raise ModuleNotFoundError(
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"[extension] PyTorch is not found while CUDA_EXT=1. You need to install PyTorch first in order to build CUDA extensions"
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)
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if not CUDA_HOME:
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raise RuntimeError(
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"[extension] CUDA_HOME is not found while CUDA_EXT=1. You need to export CUDA_HOME environment vairable or install CUDA Toolkit first in order to build CUDA extensions"
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)
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check_system_pytorch_cuda_match(CUDA_HOME)
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check_pytorch_version(MIN_PYTORCH_VERSION_MAJOR, MIN_PYTORCH_VERSION_MINOR)
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check_cuda_availability()
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def fetch_requirements(path) -> List[str]:
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"""
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This function reads the requirements file.
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Args:
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path (str): the path to the requirements file.
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Returns:
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The lines in the requirements file.
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"""
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with open(path, 'r') as fd:
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return [r.strip() for r in fd.readlines()]
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def fetch_readme() -> str:
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"""
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This function reads the README.md file in the current directory.
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Returns:
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The lines in the README file.
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"""
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with open('README.md', encoding='utf-8') as f:
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return f.read()
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def get_version() -> str:
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"""
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This function reads the version.txt and generates the colossalai/version.py file.
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Returns:
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The library version stored in version.txt.
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"""
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setup_file_path = os.path.abspath(__file__)
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project_path = os.path.dirname(setup_file_path)
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version_txt_path = os.path.join(project_path, 'version.txt')
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version_py_path = os.path.join(project_path, 'colossalai/version.py')
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with open(version_txt_path) as f:
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version = f.read().strip()
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# write version into version.py
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with open(version_py_path, 'w') as f:
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f.write(f"__version__ = '{version}'\n")
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# look for pytorch and cuda version
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if BUILD_CUDA_EXT:
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torch_major, torch_minor, _ = get_pytorch_version()
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torch_version = f'{torch_major}.{torch_minor}'
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cuda_version = '.'.join(get_cuda_bare_metal_version(CUDA_HOME))
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else:
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torch_version = None
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cuda_version = None
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# write the version into the python file
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if torch_version:
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f.write(f'torch = "{torch_version}"\n')
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else:
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f.write('torch = None\n')
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if cuda_version:
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f.write(f'cuda = "{cuda_version}"\n')
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else:
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f.write('cuda = None\n')
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return version
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if BUILD_CUDA_EXT:
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environment_check_for_cuda_extension_build()
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set_cuda_arch_list(CUDA_HOME)
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from op_builder import ALL_OPS
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op_names = []
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# load all builders
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for name, builder_cls in ALL_OPS.items():
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op_names.append(name)
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ext_modules.append(builder_cls().builder())
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# show log
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op_name_list = ', '.join(op_names)
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print(f"[extension] loaded builders for {op_name_list}")
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# always put not nightly branch as the if branch
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# otherwise github will treat colossalai-nightly as the project name
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# and it will mess up with the dependency graph insights
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if not IS_NIGHTLY:
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version = get_version()
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package_name = 'colossalai'
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else:
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# use date as the nightly version
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version = datetime.today().strftime('%Y.%m.%d')
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package_name = 'colossalai-nightly'
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setup(name=package_name,
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version=version,
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packages=find_packages(exclude=(
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'op_builder',
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'benchmark',
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'docker',
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'tests',
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'docs',
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'examples',
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'tests',
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'scripts',
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'requirements',
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'*.egg-info',
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)),
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description='An integrated large-scale model training system with efficient parallelization techniques',
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long_description=fetch_readme(),
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long_description_content_type='text/markdown',
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license='Apache Software License 2.0',
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url='https://www.colossalai.org',
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project_urls={
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'Forum': 'https://github.com/hpcaitech/ColossalAI/discussions',
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'Bug Tracker': 'https://github.com/hpcaitech/ColossalAI/issues',
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'Examples': 'https://github.com/hpcaitech/ColossalAI-Examples',
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'Documentation': 'http://colossalai.readthedocs.io',
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'Github': 'https://github.com/hpcaitech/ColossalAI',
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},
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ext_modules=ext_modules,
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cmdclass={'build_ext': BuildExtension} if ext_modules else {},
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install_requires=fetch_requirements('requirements/requirements.txt'),
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entry_points='''
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[console_scripts]
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colossalai=colossalai.cli:cli
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''',
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python_requires='>=3.6',
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classifiers=[
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'Programming Language :: Python :: 3',
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'License :: OSI Approved :: Apache Software License',
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'Environment :: GPU :: NVIDIA CUDA',
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'Topic :: Scientific/Engineering :: Artificial Intelligence',
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'Topic :: System :: Distributed Computing',
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],
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package_data={
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'colossalai': [
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'_C/*.pyi', 'kernel/cuda_native/csrc/*', 'kernel/cuda_native/csrc/kernel/*',
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'kernel/cuda_native/csrc/kernels/include/*'
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]
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})
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