example-apps/PDD/pcb-defect-detection/libs/setup.py

   1 # --------------------------------------------------------
   2 # Fast R-CNN
   3 # Copyright (c) 2015 Microsoft
   4 # Licensed under The MIT License [see LICENSE for details]
   5 # Written by Ross Girshick
   6 # --------------------------------------------------------
   7
   8 import os
   9 from os.path import join as pjoin
  10 from setuptools import setup
  11 from distutils.extension import Extension
  12 from Cython.Distutils import build_ext
  13 import subprocess
  14 import numpy as np
  15
  16
  17 def find_in_path(name, path):
  18     "Find a file in a search path"
  19     # Adapted fom
  20     # http://code.activestate.com/recipes/52224-find-a-file-given-a-search-path/
  21     for dir in path.split(os.pathsep):
  22         binpath = pjoin(dir, name)
  23         if os.path.exists(binpath):
  24             return os.path.abspath(binpath)
  25     return None
  26
  27
  28 def locate_cuda():
  29     """Locate the CUDA environment on the system
  30
  31     Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64'
  32     and values giving the absolute path to each directory.
  33
  34     Starts by looking for the CUDAHOME env variable. If not found, everything
  35     is based on finding 'nvcc' in the PATH.
  36     """
  37
  38     # first check if the CUDAHOME env variable is in use
  39     if 'CUDAHOME' in os.environ:
  40         home = os.environ['CUDAHOME']
  41         nvcc = pjoin(home, 'bin', 'nvcc')
  42     else:
  43         # otherwise, search the PATH for NVCC
  44         default_path = pjoin(os.sep, 'usr', 'local', 'cuda', 'bin')
  45         nvcc = find_in_path('nvcc', os.environ['PATH'] + os.pathsep + default_path)
  46         if nvcc is None:
  47             raise EnvironmentError('The nvcc binary could not be '
  48                 'located in your $PATH. Either add it to your path, or set $CUDAHOME')
  49         home = os.path.dirname(os.path.dirname(nvcc))
  50
  51     cudaconfig = {'home':home, 'nvcc':nvcc,
  52                   'include': pjoin(home, 'include'),
  53                   'lib64': pjoin(home, 'lib64')}
  54     for k, v in cudaconfig.iteritems():
  55         if not os.path.exists(v):
  56             raise EnvironmentError('The CUDA %s path could not be located in %s' % (k, v))
  57
  58     return cudaconfig
  59 CUDA = locate_cuda()
  60
  61
  62 # Obtain the numpy include directory.  This logic works across numpy versions.
  63 try:
  64     numpy_include = np.get_include()
  65 except AttributeError:
  66     numpy_include = np.get_numpy_include()
  67
  68
  69 def customize_compiler_for_nvcc(self):
  70     """inject deep into distutils to customize how the dispatch
  71     to gcc/nvcc works.
  72
  73     If you subclass UnixCCompiler, it's not trivial to get your subclass
  74     injected in, and still have the right customizations (i.e.
  75     distutils.sysconfig.customize_compiler) run on it. So instead of going
  76     the OO route, I have this. Note, it's kindof like a wierd functional
  77     subclassing going on."""
  78
  79     # tell the compiler it can processes .cu
  80     self.src_extensions.append('.cu')
  81
  82     # save references to the default compiler_so and _comple methods
  83     default_compiler_so = self.compiler_so
  84     super = self._compile
  85
  86     # now redefine the _compile method. This gets executed for each
  87     # object but distutils doesn't have the ability to change compilers
  88     # based on source extension: we add it.
  89     def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
  90         if os.path.splitext(src)[1] == '.cu':
  91             # use the cuda for .cu files
  92             self.set_executable('compiler_so', CUDA['nvcc'])
  93             # use only a subset of the extra_postargs, which are 1-1 translated
  94             # from the extra_compile_args in the Extension class
  95             postargs = extra_postargs['nvcc']
  96         else:
  97             postargs = extra_postargs['gcc']
  98
  99         super(obj, src, ext, cc_args, postargs, pp_opts)
 100         # reset the default compiler_so, which we might have changed for cuda
 101         self.compiler_so = default_compiler_so
 102
 103     # inject our redefined _compile method into the class
 104     self._compile = _compile
 105
 106
 107 # run the customize_compiler
 108 class custom_build_ext(build_ext):
 109     def build_extensions(self):
 110         customize_compiler_for_nvcc(self.compiler)
 111         build_ext.build_extensions(self)
 112
 113
 114 ext_modules = [
 115     # Extension(
 116     #     "utils.cython_bbox",
 117     #     ["utils/bbox.pyx"],
 118     #     extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]},
 119     #     include_dirs = [numpy_include]
 120     # ),
 121     # Extension(
 122     #     "nms.cpu_nms",
 123     #     ["nms/cpu_nms.pyx"],
 124     #     extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]},
 125     #     include_dirs = [numpy_include]
 126     # ),
 127     #
 128     # Extension(
 129     #     "rotation.rotate_cython_nms",
 130     #     ["rotation/rotate_cython_nms.pyx"],
 131     #     extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]},
 132     #     include_dirs = [numpy_include]
 133     # ),
 134     #
 135     # Extension(
 136     #     "rotation.rotate_circle_nms",
 137     #     ["rotation/rotate_circle_nms.pyx"],
 138     #     extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]},
 139     #     include_dirs = [numpy_include]
 140     # ),
 141     #
 142     # Extension('nms.gpu_nms',
 143     #     ['nms/nms_kernel.cu', 'nms/gpu_nms.pyx'],
 144     #     library_dirs=[CUDA['lib64']],
 145     #     libraries=['cudart'],
 146     #     language='c++',
 147     #     runtime_library_dirs=[CUDA['lib64']],
 148     #     # this syntax is specific to this build system
 149     #     # we're only going to use certain compiler args with nvcc and not with
 150     #     # gcc the implementation of this trick is in customize_compiler() below
 151     #     extra_compile_args={'gcc': ["-Wno-unused-function"],
 152     #                         'nvcc': ['-arch=sm_35',
 153     #                                  '--ptxas-options=-v',
 154     #                                  '-c',
 155     #                                  '--compiler-options',
 156     #                                  "'-fPIC'"]},
 157     #     include_dirs = [numpy_include, CUDA['include']]
 158     # ),
 159     # Extension('rotation.rotate_gpu_nms',
 160     #     ['rotation/rotate_nms_kernel.cu', 'rotation/rotate_gpu_nms.pyx'],
 161     #     library_dirs=[CUDA['lib64']],
 162     #     libraries=['cudart'],
 163     #     language='c++',
 164     #     runtime_library_dirs=[CUDA['lib64']],
 165     #     # this syntax is specific to this build system
 166     #     # we're only going to use certain compiler args with nvcc anrbd not with
 167     #     # gcc the implementation of this trick is in customize_compiler() below
 168     #     extra_compile_args={'gcc': ["-Wno-unused-function"],
 169     #                         'nvcc': ['-arch=sm_35',
 170     #                                  '--ptxas-options=-v',
 171     #                                  '-c',
 172     #                                  '--compiler-options',
 173     #                                  "'-fPIC'"]},
 174     #     include_dirs = [numpy_include, CUDA['include']]
 175     # ),
 176     Extension('rotation.rbbox_overlaps',
 177         ['rotation/rbbox_overlaps_kernel.cu', 'rotation/rbbox_overlaps.pyx'],
 178         library_dirs=[CUDA['lib64']],
 179         libraries=['cudart'],
 180         language='c++',
 181         runtime_library_dirs=[CUDA['lib64']],
 182         # this syntax is specific to this build system
 183         # we're only going to use certain compiler args with nvcc and not with
 184         # gcc the implementation of this trick is in customize_compiler() below
 185         extra_compile_args={'gcc': ["-Wno-unused-function"],
 186                             'nvcc': ['-arch=sm_35',
 187                                      '--ptxas-options=-v',
 188                                      '-c',
 189                                      '--compiler-options',
 190                                      "'-fPIC'"]},
 191         include_dirs = [numpy_include, CUDA['include']]
 192     ),
 193     # Extension('rotation.rotate_polygon_nms',
 194     #     ['rotation/rotate_polygon_nms_kernel.cu', 'rotation/rotate_polygon_nms.pyx'],
 195     #     library_dirs=[CUDA['lib64']],
 196     #     libraries=['cudart'],
 197     #     language='c++',
 198     #     runtime_library_dirs=[CUDA['lib64']],
 199     #     # this syntax is specific to this build system
 200     #     # we're only going to use certain compiler args with nvcc and not with
 201     #     # gcc the implementation of this trick is in customize_compiler() below
 202     #     extra_compile_args={'gcc': ["-Wno-unused-function"],
 203     #                         'nvcc': ['-arch=sm_35',
 204     #                                  '--ptxas-options=-v',
 205     #                                  '-c',
 206     #                                  '--compiler-options',
 207     #                                  "'-fPIC'"]},
 208     #     include_dirs = [numpy_include, CUDA['include']]
 209     # ),
 210     #
 211     # Extension(
 212     #     'pycocotools._mask',
 213     #     sources=['pycocotools/maskApi.c', 'pycocotools/_mask.pyx'],
 214     #     include_dirs = [numpy_include, 'pycocotools'],
 215     #     extra_compile_args={
 216     #         'gcc': ['-Wno-cpp', '-Wno-unused-function', '-std=c99']},
 217     # ),
 218 ]
 219
 220 setup(
 221     name='fast_rcnn',
 222     ext_modules=ext_modules,
 223     # inject our custom trigger
 224     cmdclass={'build_ext': custom_build_ext},
 225 )