text: #!/usr/bin/env python
  # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
  
  import glob
  import os
  import runpy
  import warnings
  
  import torch
  from setuptools import find_packages, setup
  from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension
  
  
  def get_extensions():
      this_dir = os.path.dirname(os.path.abspath(__file__))
      extensions_dir = os.path.join(this_dir, "pytorch3d", "csrc")
      sources = glob.glob(os.path.join(extensions_dir, "**", "*.cpp"), recursive=True)
      source_cuda = glob.glob(os.path.join(extensions_dir, "**", "*.cu"), recursive=True)
      extension = CppExtension
  
      extra_compile_args = {"cxx": ["-std=c++14"]}
      define_macros = []
  
      force_cuda = os.getenv("FORCE_CUDA", "0") == "1"
      if (torch.cuda.is_available() and CUDA_HOME is not None) or force_cuda:
          extension = CUDAExtension
          sources += source_cuda
          define_macros += [("WITH_CUDA", None)]
          cub_home = os.environ.get("CUB_HOME", None)
          nvcc_args = [
              "-std=c++14",
              "-DCUDA_HAS_FP16=1",
              "-D__CUDA_NO_HALF_OPERATORS__",
              "-D__CUDA_NO_HALF_CONVERSIONS__",
              "-D__CUDA_NO_HALF2_OPERATORS__",
          ]
          if cub_home is None:
              warnings.warn(
                  "The environment variable `CUB_HOME` was not found. "
                  "NVIDIA CUB is required for compilation and can be downloaded "
                  "from `https://github.com/NVIDIA/cub/releases`. You can unpack "
                  "it to a location of your choice and set the environment variable "
                  "`CUB_HOME` to the folder containing the `CMakeListst.txt` file."
              )
          else:
              nvcc_args.insert(
                  0, "-I%s" % (os.path.realpath(cub_home).replace("\\ ", " "))
              )
          nvcc_flags_env = os.getenv("NVCC_FLAGS", "")
          if nvcc_flags_env != "":
              nvcc_args.extend(nvcc_flags_env.split(" "))
  
          # It's better if pytorch can do this by default ..
          CC = os.environ.get("CC", None)
          if CC is not None:
              CC_arg = "-ccbin={}".format(CC)
              if CC_arg not in nvcc_args:
                  if any(arg.startswith("-ccbin") for arg in nvcc_args):
                      raise ValueError("Inconsistent ccbins")
                  nvcc_args.append(CC_arg)
  
          extra_compile_args["nvcc"] = nvcc_args
  
      sources = [os.path.join(extensions_dir, s) for s in sources]
  
      include_dirs = [extensions_dir]
  
      ext_modules = [
          extension(
              "pytorch3d._C",
              sources,
              include_dirs=include_dirs,
              define_macros=define_macros,
              extra_compile_args=extra_compile_args,
          )
      ]
  
      return ext_modules
  
  
  # Retrieve __version__ from the package.
  __version__ = runpy.run_path("pytorch3d/__init__.py")["__version__"]
  
  
  if os.getenv("PYTORCH3D_NO_NINJA", "0") == "1":
  
      class BuildExtension(torch.utils.cpp_extension.BuildExtension):
          def __init__(self, *args, **kwargs):
              super().__init__(use_ninja=False, *args, **kwargs)
  
  
  else:
      BuildExtension = torch.utils.cpp_extension.BuildExtension
  
  
  setup(
      name="pytorch3d",
      version=__version__,
      author="FAIR",
      url="https://github.com/facebookresearch/pytorch3d",
      description="PyTorch3D is FAIR's library of reusable components "
      "for deep Learning with 3D data.",
      packages=find_packages(exclude=("configs", "tests")),
      install_requires=["torchvision>=0.4", "fvcore"],
      extras_require={
          "all": ["matplotlib", "tqdm>4.29.0", "imageio", "ipywidgets"],
          "dev": ["flake8", "isort", "black==19.3b0"],
      },
      ext_modules=get_extensions(),
      cmdclass={"build_ext": BuildExtension},
  )
  