56 lines
1.5 KiB
Python
56 lines
1.5 KiB
Python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
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# !/usr/bin/env python
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# reference: https://github.com/facebookresearch/maskrcnn-benchmark/blob/90c226cf10e098263d1df28bda054a5f22513b4f/setup.py
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import os
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import glob
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import torch
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from setuptools import setup
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from torch.utils.cpp_extension import BuildExtension, CppExtension, CUDAExtension, CUDA_HOME
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requirements = ["torch"]
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def get_extension():
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this_dir = os.path.dirname(os.path.abspath(__file__))
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extensions_dir = os.path.join(this_dir, "csrc")
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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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define_macros = []
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if (torch.cuda.is_available() and CUDA_HOME is not None) or os.getenv("FORCE_CUDA", "0") == "1":
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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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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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"._C",
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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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)
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]
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return ext_modules
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setup(
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name="semantic_segmentation",
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version="0.1",
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author="tramac",
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description="semantic segmentation in pytorch",
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ext_modules=get_extension(),
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cmdclass={"build_ext": BuildExtension}
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) |