# -------------------------------------------------------- # Fast R-CNN # Copyright (c) 2015 Microsoft # Licensed under The MIT License [see LICENSE for details] # Written by Ross Girshick # -------------------------------------------------------- import os from os.path import join as pjoin from setuptools import setup from distutils.extension import Extension from Cython.Distutils import build_ext import subprocess import numpy as np def find_in_path(name, path): "Find a file in a search path" # Adapted fom # http://code.activestate.com/recipes/52224-find-a-file-given-a-search-path/ for dir in path.split(os.pathsep): binpath = pjoin(dir, name) if os.path.exists(binpath): return os.path.abspath(binpath) return None def locate_cuda(): """Locate the CUDA environment on the system Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64' and values giving the absolute path to each directory. Starts by looking for the CUDAHOME env variable. If not found, everything is based on finding 'nvcc' in the PATH. """ # first check if the CUDAHOME env variable is in use if 'CUDAHOME' in os.environ: home = os.environ['CUDAHOME'] nvcc = pjoin(home, 'bin', 'nvcc') else: # otherwise, search the PATH for NVCC default_path = pjoin(os.sep, 'usr', 'local', 'cuda', 'bin') nvcc = find_in_path('nvcc', os.environ['PATH'] + os.pathsep + default_path) if nvcc is None: raise EnvironmentError('The nvcc binary could not be ' 'located in your $PATH. Either add it to your path, or set $CUDAHOME') home = os.path.dirname(os.path.dirname(nvcc)) cudaconfig = {'home':home, 'nvcc':nvcc, 'include': pjoin(home, 'include'), 'lib64': pjoin(home, 'lib64')} for k, v in cudaconfig.iteritems(): if not os.path.exists(v): raise EnvironmentError('The CUDA %s path could not be located in %s' % (k, v)) return cudaconfig CUDA = locate_cuda() # Obtain the numpy include directory. This logic works across numpy versions. try: numpy_include = np.get_include() except AttributeError: numpy_include = np.get_numpy_include() def customize_compiler_for_nvcc(self): """inject deep into distutils to customize how the dispatch to gcc/nvcc works. If you subclass UnixCCompiler, it's not trivial to get your subclass injected in, and still have the right customizations (i.e. distutils.sysconfig.customize_compiler) run on it. So instead of going the OO route, I have this. Note, it's kindof like a wierd functional subclassing going on.""" # tell the compiler it can processes .cu self.src_extensions.append('.cu') # save references to the default compiler_so and _comple methods default_compiler_so = self.compiler_so super = self._compile # now redefine the _compile method. This gets executed for each # object but distutils doesn't have the ability to change compilers # based on source extension: we add it. def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts): if os.path.splitext(src)[1] == '.cu': # use the cuda for .cu files self.set_executable('compiler_so', CUDA['nvcc']) # use only a subset of the extra_postargs, which are 1-1 translated # from the extra_compile_args in the Extension class postargs = extra_postargs['nvcc'] else: postargs = extra_postargs['gcc'] super(obj, src, ext, cc_args, postargs, pp_opts) # reset the default compiler_so, which we might have changed for cuda self.compiler_so = default_compiler_so # inject our redefined _compile method into the class self._compile = _compile # run the customize_compiler class custom_build_ext(build_ext): def build_extensions(self): customize_compiler_for_nvcc(self.compiler) build_ext.build_extensions(self) ext_modules = [ # Extension( # "utils.cython_bbox", # ["utils/bbox.pyx"], # extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]}, # include_dirs = [numpy_include] # ), # Extension( # "nms.cpu_nms", # ["nms/cpu_nms.pyx"], # extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]}, # include_dirs = [numpy_include] # ), # # Extension( # "rotation.rotate_cython_nms", # ["rotation/rotate_cython_nms.pyx"], # extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]}, # include_dirs = [numpy_include] # ), # # Extension( # "rotation.rotate_circle_nms", # ["rotation/rotate_circle_nms.pyx"], # extra_compile_args={'gcc': ["-Wno-cpp", "-Wno-unused-function"]}, # include_dirs = [numpy_include] # ), # # Extension('nms.gpu_nms', # ['nms/nms_kernel.cu', 'nms/gpu_nms.pyx'], # library_dirs=[CUDA['lib64']], # libraries=['cudart'], # language='c++', # runtime_library_dirs=[CUDA['lib64']], # # this syntax is specific to this build system # # we're only going to use certain compiler args with nvcc and not with # # gcc the implementation of this trick is in customize_compiler() below # extra_compile_args={'gcc': ["-Wno-unused-function"], # 'nvcc': ['-arch=sm_35', # '--ptxas-options=-v', # '-c', # '--compiler-options', # "'-fPIC'"]}, # include_dirs = [numpy_include, CUDA['include']] # ), # Extension('rotation.rotate_gpu_nms', # ['rotation/rotate_nms_kernel.cu', 'rotation/rotate_gpu_nms.pyx'], # library_dirs=[CUDA['lib64']], # libraries=['cudart'], # language='c++', # runtime_library_dirs=[CUDA['lib64']], # # this syntax is specific to this build system # # we're only going to use certain compiler args with nvcc anrbd not with # # gcc the implementation of this trick is in customize_compiler() below # extra_compile_args={'gcc': ["-Wno-unused-function"], # 'nvcc': ['-arch=sm_35', # '--ptxas-options=-v', # '-c', # '--compiler-options', # "'-fPIC'"]}, # include_dirs = [numpy_include, CUDA['include']] # ), Extension('rotation.rbbox_overlaps', ['rotation/rbbox_overlaps_kernel.cu', 'rotation/rbbox_overlaps.pyx'], library_dirs=[CUDA['lib64']], libraries=['cudart'], language='c++', runtime_library_dirs=[CUDA['lib64']], # this syntax is specific to this build system # we're only going to use certain compiler args with nvcc and not with # gcc the implementation of this trick is in customize_compiler() below extra_compile_args={'gcc': ["-Wno-unused-function"], 'nvcc': ['-arch=sm_35', '--ptxas-options=-v', '-c', '--compiler-options', "'-fPIC'"]}, include_dirs = [numpy_include, CUDA['include']] ), # Extension('rotation.rotate_polygon_nms', # ['rotation/rotate_polygon_nms_kernel.cu', 'rotation/rotate_polygon_nms.pyx'], # library_dirs=[CUDA['lib64']], # libraries=['cudart'], # language='c++', # runtime_library_dirs=[CUDA['lib64']], # # this syntax is specific to this build system # # we're only going to use certain compiler args with nvcc and not with # # gcc the implementation of this trick is in customize_compiler() below # extra_compile_args={'gcc': ["-Wno-unused-function"], # 'nvcc': ['-arch=sm_35', # '--ptxas-options=-v', # '-c', # '--compiler-options', # "'-fPIC'"]}, # include_dirs = [numpy_include, CUDA['include']] # ), # # Extension( # 'pycocotools._mask', # sources=['pycocotools/maskApi.c', 'pycocotools/_mask.pyx'], # include_dirs = [numpy_include, 'pycocotools'], # extra_compile_args={ # 'gcc': ['-Wno-cpp', '-Wno-unused-function', '-std=c99']}, # ), ] setup( name='fast_rcnn', ext_modules=ext_modules, # inject our custom trigger cmdclass={'build_ext': custom_build_ext}, )