构建快速 RCNN 时 GCC 链接错误

问题描述

我正在尝试在 https://github.com/craftGBD/craftGBD 构建源代码，以达到与作者发表的论文相同的结果，以观察它对于我的学期项目是否可重现。我意识到我必须通过在craftGBD/evaluation/lib 文件夹中运行Makefile 来安装Fast RCNN。但是，当我使用 make 运行 Makefile 时，我得到了以下结果：

/cta/users/byaman/craftEnv/bin/python setup.py build_ext --inplace
python setup.py build_ext --inplace
running build_ext
cythoning utils/bBox.pyx to utils/bBox.c
/cta/users/byaman/craftEnv/lib/python2.7/site-packages/Cython/Compiler/Main.py:369: FutureWarning: Cython directive 'language_level' not set,using 2 for Now (Py2). This will change in a later release! File: /cta/users/byaman/craftGBD/evaluation/lib/utils/bBox.pyx
  tree = Parsing.p_module(s,pxd,full_module_name)
cythoning nms/cpu_nms.pyx to nms/cpu_nms.c
/cta/users/byaman/craftEnv/lib/python2.7/site-packages/Cython/Compiler/Main.py:369: FutureWarning: Cython directive 'language_level' not set,using 2 for Now (Py2). This will change in a later release! File: /cta/users/byaman/craftGBD/evaluation/lib/nms/cpu_nms.pyx
  tree = Parsing.p_module(s,full_module_name)
cythoning nms/gpu_nms.pyx to nms/gpu_nms.cpp
/cta/users/byaman/craftEnv/lib/python2.7/site-packages/Cython/Compiler/Main.py:369: FutureWarning: Cython directive 'language_level' not set,using 2 for Now (Py2). This will change in a later release! File: /cta/users/byaman/craftGBD/evaluation/lib/nms/gpu_nms.pyx
  tree = Parsing.p_module(s,full_module_name)
skipping 'pycocotools/_mask.c' Cython extension (up-to-date)
building 'utils.cython_bBox' extension
['-Wno-cpp','-Wno-unused-function'] .c ['-I/cta/users/byaman/craftEnv/lib/python2.7/site-packages/numpy/core/include','-I/cta/users/byaman/craftEnv/include/python2.7','-c'] ['-Wno-cpp','-Wno-unused-function'] ['-I/cta/users/byaman/craftEnv/lib/python2.7/site-packages/numpy/core/include','-I/cta/users/byaman/craftEnv/include/python2.7']
/cta/users/byaman/craftEnv/bin/x86_64-conda-linux-gnu-cc -fno-strict-aliasing -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O3 -pipe -DNDEBUG -fwrapv -O3 -Wall -Wstrict-prototypes -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /cta/users/byaman/craftEnv/include -I/cta/apps/opt/spack/linux-ubuntu18.04-cascadelake/gcc-10.2.0/cuda-10.0.130-zjercki4memwdfwjztmfkq2yio2jcev4/include -DNDEBUG -D_FORTIFY_SOURCE=2 -O2 -isystem /cta/users/byaman/craftEnv/include -I/cta/apps/opt/spack/linux-ubuntu18.04-cascadelake/gcc-10.2.0/cuda-10.0.130-zjercki4memwdfwjztmfkq2yio2jcev4/include -fPIC -I/cta/users/byaman/craftEnv/lib/python2.7/site-packages/numpy/core/include -I/cta/users/byaman/craftEnv/include/python2.7 -c utils/bBox.c -o build/temp.linux-x86_64-2.7/utils/bBox.o -Wno-cpp -Wno-unused-function
x86_64-conda_cos6-linux-gnu-gcc -pthread -shared -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,Now -Wl,-rpath,/cta/users/byaman/craftEnv/lib -L/cta/users/byaman/craftEnv/lib -Wl,--no-as-needed -Wl,--disable-new-dtags -Wl,--gc-sections -Wl,/cta/users/byaman/craftEnv/lib -Wl,-rpath-link,/cta/users/byaman/craftEnv/lib -L/cta/users/byaman/craftEnv/lib -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /cta/users/byaman/craftEnv/include -I/cta/apps/opt/spack/linux-ubuntu18.04-cascadelake/gcc-10.2.0/cuda-10.0.130-zjercki4memwdfwjztmfkq2yio2jcev4/include -DNDEBUG -D_FORTIFY_SOURCE=2 -O2 -isystem /cta/users/byaman/craftEnv/include -I/cta/apps/opt/spack/linux-ubuntu18.04-cascadelake/gcc-10.2.0/cuda-10.0.130-zjercki4memwdfwjztmfkq2yio2jcev4/include build/temp.linux-x86_64-2.7/utils/bBox.o -L/cta/users/byaman/craftEnv/lib -lpython2.7 -o /cta/users/byaman/craftGBD/evaluation/lib/utils/cython_bBox.so
/cta/users/byaman/craftEnv/bin/../lib/gcc/x86_64-conda-linux-gnu/9.3.0/../../../../x86_64-conda-linux-gnu/bin/ld: /cta/users/byaman/craftEnv/lib/libc.a(__stack_chk_fail.o): relocation R_X86_64_32 against symbol `__stack_chk_guard' can not be used when making a shared object; recompile with -fPIC
collect2: error: ld returned 1 exit status
error: command 'x86_64-conda_cos6-linux-gnu-gcc' Failed with exit status 1
Makefile:2: recipe for target 'all' Failed
make: *** [all] Error 1

请注意，我的用户名是 byaman，我在 Conda 环境中运行代码，即 craftEnv。

Makefile 运行的代码是：

# --------------------------------------------------------
# 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,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"],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(
        'pycocotools._mask',sources=['pycocotools/maskApi.c','pycocotools/_mask.pyx'],'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},)

即使我调查了以下问题/答案，我也不知道如何解决这个问题：

"relocation R_X86_64_32S against " linking Error

How to recompile with -fPIC

Cython wrapping a class that uses another library

解决方法

暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！

如果你已经找到好的解决方法，欢迎将解决方案带上本链接一起发送给小编。

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