73 lines
2.1 KiB
Python
73 lines
2.1 KiB
Python
# --------------------------------------------------------
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# InternImage
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# Copyright (c) 2022 OpenGVLab
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# Licensed under The MIT License [see LICENSE for details]
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# --------------------------------------------------------
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# Copied from
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# https://github.com/OpenGVLab/InternImage/blob/master/classification/models/
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import glob
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import os
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from setuptools import find_packages, setup
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import torch
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from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension
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requirements = ['torch', 'torchvision']
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def get_extensions():
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this_dir = os.path.dirname(os.path.abspath(__file__))
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extensions_dir = os.path.join(this_dir, 'src')
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main_file = glob.glob(os.path.join(extensions_dir, '*.cpp'))
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source_cpu = glob.glob(os.path.join(extensions_dir, 'cpu', '*.cpp'))
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source_cuda = glob.glob(os.path.join(extensions_dir, 'cuda', '*.cu'))
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sources = main_file + source_cpu
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extension = CppExtension
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extra_compile_args = {'cxx': []}
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define_macros = []
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if torch.cuda.is_available() and CUDA_HOME is not None:
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extension = CUDAExtension
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sources += source_cuda
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define_macros += [('WITH_CUDA', None)]
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extra_compile_args['nvcc'] = [
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# "-DCUDA_HAS_FP16=1",
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# "-D__CUDA_NO_HALF_OPERATORS__",
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# "-D__CUDA_NO_HALF_CONVERSIONS__",
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# "-D__CUDA_NO_HALF2_OPERATORS__",
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]
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else:
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raise NotImplementedError('Cuda is not availabel')
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sources = [os.path.join(extensions_dir, s) for s in sources]
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include_dirs = [extensions_dir]
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ext_modules = [
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extension(
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'DCNv3',
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sources,
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include_dirs=include_dirs,
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define_macros=define_macros,
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extra_compile_args=extra_compile_args,
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)
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]
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return ext_modules
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setup(
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name='DCNv3',
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version='1.1',
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author='InternImage',
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url='https://github.com/OpenGVLab/InternImage',
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description='PyTorch Wrapper for CUDA Functions of DCNv3',
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packages=find_packages(exclude=(
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'configs',
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'tests',
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)),
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ext_modules=get_extensions(),
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cmdclass={'build_ext': torch.utils.cpp_extension.BuildExtension},
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)
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