mirror of https://github.com/hpcaitech/ColossalAI
aibig-modeldata-parallelismdeep-learningdistributed-computingfoundation-modelsheterogeneous-traininghpcinferencelarge-scalemodel-parallelismpipeline-parallelism
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198 lines
6.1 KiB
198 lines
6.1 KiB
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 variable 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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