質問編集履歴

コードのURLと変更箇所の追記

2020/12/20 13:32

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shosin__

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@@ -54,306 +54,40 @@
-・setup.pyのコード
+参考コードのURL
-```python
-import numpy as np
-import os
-from os.path import join as pjoin
-#from distutils.core import setup
-from setuptools import setup
-from distutils.extension import Extension
-from Cython.Distutils import build_ext
+https://github.com/qijiezhao/M2Det
-import subprocess
-#change for windows, by MrX
+変更箇所
-nvcc_bin = 'nvcc.exe'
+・setup.py
+　61行目を変更
+　変更前：for k, v in cudaconfig.iteritems():
-lib_dir = 'lib/x64'
+　変更後：for k, v in cudaconfig.items():
-def find_in_path(name, path):
-    "Find a file in a search path"
-    # Adapted fom
+　128～136行目をコメントアウト
-    # 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
+・setup_cuda.py
+　61行目を変更
-def locate_cuda():
+　変更前：nvcc_compile_args = ['-O', '--ptxas-options=-v', '-arch=sm_35', '-c', '--compiler-options=-fPIC']
-    """Locate the CUDA environment on the system
+　変更後：nvcc_compile_args = ['-O2', '--ptxas-options=-v', '-arch=sm_35', '-c', '--compiler-options=-fPIC']
-    Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64'
+　100行目と101行目の間に以下を追記
-    and values giving the absolute path to each directory.
+　　 #Remove ',ID=2'
-    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 'CUDA_PATH' in os.environ:
+    elif ',ID=2' in c: cmd[idx] = c[0:len(c)-5]
-        home = os.environ['CUDA_PATH']
-        print("home = %s\n" % home)
-        nvcc = pjoin(home, 'bin', nvcc_bin)
-    else:
-        # otherwise, search the PATH for NVCC
-        default_path = pjoin(os.sep, 'usr', 'local', 'cuda', 'bin')
-        nvcc = find_in_path(nvcc_bin, 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 $CUDA_PATH')
-        home = os.path.dirname(os.path.dirname(nvcc))
-        print("home = %s, nvcc = %s\n" % (home, nvcc))
-    cudaconfig = {'home':home, 'nvcc':nvcc,
-                  'include': pjoin(home, 'include'),
-                  'lib64': pjoin(home, lib_dir)}
-#    for k, v in cudaconfig.iteritems():
-    for k, v in cudaconfig.items():
-        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.spawn
-    #default_compiler_so = self.rc
-    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(sources, output_dir=None, macros=None, include_dirs=None, debug=0, extra_preargs=None, extra_postargs=None, depends=None):
-        postfix=os.path.splitext(sources[0])[1]
-        if postfix == '.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']
-        return super(sources, output_dir, macros, include_dirs, debug, extra_preargs, postargs, depends)
-        # reset the default compiler_so, which we might have changed for cuda
-        #self.rc = 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 = [
-    # unix _compile: obj, src, ext, cc_args, extra_postargs, pp_opts
-    Extension(
-        "utils.cython_bbox",
-        sources=["utils\bbox.pyx"],
-        #define_macros={'/LD'},
-        #extra_compile_args={'gcc': ['/link', '/DLL', '/OUT:cython_bbox.dll']},
-        #extra_compile_args={'gcc': ['/LD']},
-        extra_compile_args={'gcc': []},
-        include_dirs = [numpy_include]
-    ),
-    Extension(
-        "nms.cpu_nms",
-        sources=["nms\cpu_nms.pyx"],
-        extra_compile_args={'gcc': []},
-        include_dirs = [numpy_include],
-    ),
-    Extension(
-        "pycocotools._mask",
-        sources=['pycocotools\maskApi.c', 'pycocotools\_mask.pyx'],
-        include_dirs = [numpy_include, 'pycocotools'],
-        extra_compile_args={
-            'gcc': ['/Qstd=c99']},
-    ),
-    #Extension(   # just used to get nms\gpu_nms.obj
-    #    "nms.gpu_nms",
-    #    sources=['nms\gpu_nms.pyx'],
-    #    language='c++',
-    #    extra_compile_args={'gcc': []},
-    #    include_dirs = [numpy_include]
-    #),
-]
-setup(
-    name='fast_rcnn',
-    ext_modules=ext_modules,
-    # inject our custom trigger
-    cmdclass={'build_ext': custom_build_ext},
-)
-```

コード編集

2020/12/20 13:32

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shosin__

スコア6

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@@ -56,8 +56,6 @@
 ・setup.pyのコード
 ```python
 import numpy as np
@@ -355,3 +353,7 @@
     cmdclass={'build_ext': custom_build_ext},
 )
+```

コードを追加

2020/12/19 22:30

投稿

shosin__

スコア6

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@@ -51,3 +51,307 @@
 というエラーが出ました。
 初心者なので、できるだけわかりやすく教えていただけると幸いです。
+・setup.pyのコード
+```python
+import numpy as np
+import os
+from os.path import join as pjoin
+#from distutils.core import setup
+from setuptools import setup
+from distutils.extension import Extension
+from Cython.Distutils import build_ext
+import subprocess
+#change for windows, by MrX
+nvcc_bin = 'nvcc.exe'
+lib_dir = 'lib/x64'
+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 'CUDA_PATH' in os.environ:
+        home = os.environ['CUDA_PATH']
+        print("home = %s\n" % home)
+        nvcc = pjoin(home, 'bin', nvcc_bin)
+    else:
+        # otherwise, search the PATH for NVCC
+        default_path = pjoin(os.sep, 'usr', 'local', 'cuda', 'bin')
+        nvcc = find_in_path(nvcc_bin, 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 $CUDA_PATH')
+        home = os.path.dirname(os.path.dirname(nvcc))
+        print("home = %s, nvcc = %s\n" % (home, nvcc))
+    cudaconfig = {'home':home, 'nvcc':nvcc,
+                  'include': pjoin(home, 'include'),
+                  'lib64': pjoin(home, lib_dir)}
+#    for k, v in cudaconfig.iteritems():
+    for k, v in cudaconfig.items():
+        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.spawn
+    #default_compiler_so = self.rc
+    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(sources, output_dir=None, macros=None, include_dirs=None, debug=0, extra_preargs=None, extra_postargs=None, depends=None):
+        postfix=os.path.splitext(sources[0])[1]
+        if postfix == '.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']
+        return super(sources, output_dir, macros, include_dirs, debug, extra_preargs, postargs, depends)
+        # reset the default compiler_so, which we might have changed for cuda
+        #self.rc = 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 = [
+    # unix _compile: obj, src, ext, cc_args, extra_postargs, pp_opts
+    Extension(
+        "utils.cython_bbox",
+        sources=["utils\bbox.pyx"],
+        #define_macros={'/LD'},
+        #extra_compile_args={'gcc': ['/link', '/DLL', '/OUT:cython_bbox.dll']},
+        #extra_compile_args={'gcc': ['/LD']},
+        extra_compile_args={'gcc': []},
+        include_dirs = [numpy_include]
+    ),
+    Extension(
+        "nms.cpu_nms",
+        sources=["nms\cpu_nms.pyx"],
+        extra_compile_args={'gcc': []},
+        include_dirs = [numpy_include],
+    ),
+    Extension(
+        "pycocotools._mask",
+        sources=['pycocotools\maskApi.c', 'pycocotools\_mask.pyx'],
+        include_dirs = [numpy_include, 'pycocotools'],
+        extra_compile_args={
+            'gcc': ['/Qstd=c99']},
+    ),
+    #Extension(   # just used to get nms\gpu_nms.obj
+    #    "nms.gpu_nms",
+    #    sources=['nms\gpu_nms.pyx'],
+    #    language='c++',
+    #    extra_compile_args={'gcc': []},
+    #    include_dirs = [numpy_include]
+    #),
+]
+setup(
+    name='fast_rcnn',
+    ext_modules=ext_modules,
+    # inject our custom trigger
+    cmdclass={'build_ext': custom_build_ext},
+)

コードを追記しました。

2020/12/19 22:29

投稿

shosin__

スコア6

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