mirror of
https://github.com/facebookresearch/pytorch3d.git
synced 2025-08-01 03:12:49 +08:00
039e02601d
Summary: This diff updates the documentation and tutorials with information about the new pulsar backend. For more information about the pulsar backend, see the release notes and the paper (https://arxiv.org/abs/2004.07484). For information on how to use the backend, see the point cloud rendering notebook and the examples in the folder docs/examples. Reviewed By: nikhilaravi Differential Revision: D24498129 fbshipit-source-id: e312b0169a72b13590df6e4db36bfe6190d742f9
112 lines
3.7 KiB
Python
Executable File
112 lines
3.7 KiB
Python
Executable File
#!/usr/bin/env python
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# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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import glob
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import os
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import runpy
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import warnings
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import torch
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from setuptools import find_packages, setup
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from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension
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def get_extensions():
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this_dir = os.path.dirname(os.path.abspath(__file__))
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extensions_dir = os.path.join(this_dir, "pytorch3d", "csrc")
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sources = glob.glob(os.path.join(extensions_dir, "**", "*.cpp"), recursive=True)
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source_cuda = glob.glob(os.path.join(extensions_dir, "**", "*.cu"), recursive=True)
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extension = CppExtension
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extra_compile_args = {"cxx": ["-std=c++14"]}
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define_macros = []
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force_cuda = os.getenv("FORCE_CUDA", "0") == "1"
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if (torch.cuda.is_available() and CUDA_HOME is not None) or force_cuda:
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extension = CUDAExtension
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sources += source_cuda
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define_macros += [("WITH_CUDA", None)]
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cub_home = os.environ.get("CUB_HOME", None)
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nvcc_args = [
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"-std=c++14",
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"-DCUDA_HAS_FP16=1",
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"-D__CUDA_NO_HALF_OPERATORS__",
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"-D__CUDA_NO_HALF_CONVERSIONS__",
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"-D__CUDA_NO_HALF2_OPERATORS__",
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]
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if cub_home is None:
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warnings.warn(
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"The environment variable `CUB_HOME` was not found. "
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"NVIDIA CUB is required for compilation and can be downloaded "
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"from `https://github.com/NVIDIA/cub/releases`. You can unpack "
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"it to a location of your choice and set the environment variable "
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"`CUB_HOME` to the folder containing the `CMakeListst.txt` file."
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)
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else:
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nvcc_args.insert(
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0, "-I%s" % (os.path.realpath(cub_home).replace("\\ ", " "))
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)
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nvcc_flags_env = os.getenv("NVCC_FLAGS", "")
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if nvcc_flags_env != "":
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nvcc_args.extend(nvcc_flags_env.split(" "))
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# It's better if pytorch can do this by default ..
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CC = os.environ.get("CC", None)
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if CC is not None:
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CC_arg = "-ccbin={}".format(CC)
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if CC_arg not in nvcc_args:
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if any(arg.startswith("-ccbin") for arg in nvcc_args):
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raise ValueError("Inconsistent ccbins")
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nvcc_args.append(CC_arg)
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extra_compile_args["nvcc"] = nvcc_args
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sources = [os.path.join(extensions_dir, s) for s in sources]
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include_dirs = [extensions_dir]
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ext_modules = [
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extension(
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"pytorch3d._C",
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sources,
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include_dirs=include_dirs,
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define_macros=define_macros,
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extra_compile_args=extra_compile_args,
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)
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]
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return ext_modules
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# Retrieve __version__ from the package.
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__version__ = runpy.run_path("pytorch3d/__init__.py")["__version__"]
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if os.getenv("PYTORCH3D_NO_NINJA", "0") == "1":
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class BuildExtension(torch.utils.cpp_extension.BuildExtension):
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def __init__(self, *args, **kwargs):
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super().__init__(use_ninja=False, *args, **kwargs)
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else:
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BuildExtension = torch.utils.cpp_extension.BuildExtension
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setup(
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name="pytorch3d",
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version=__version__,
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author="FAIR",
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url="https://github.com/facebookresearch/pytorch3d",
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description="PyTorch3D is FAIR's library of reusable components "
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"for deep Learning with 3D data.",
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packages=find_packages(exclude=("configs", "tests")),
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install_requires=["torchvision>=0.4", "fvcore"],
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extras_require={
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"all": ["matplotlib", "tqdm>4.29.0", "imageio", "ipywidgets"],
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"dev": ["flake8", "isort", "black==19.3b0"],
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},
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ext_modules=get_extensions(),
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cmdclass={"build_ext": BuildExtension},
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)
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