Files
pytorch3d/setup.py
Guilherme Albertini f5f6b78e70 Add initial CUDA 13.0 support for pulsar and pycuda modules
Summary:
CUDA 13.0 introduced breaking changes that cause build failures in pytorch3d:

**1. Symbol Visibility Changes (pulsar)**
- NVCC now forces `__global__` functions to have hidden ELF visibility by default
- `__global__` function template stubs now have internal linkage

**Fix:** Added NVCC flags (`--device-entity-has-hidden-visibility=false` and `-static-global-template-stub=false`) for fbcode builds with CUDA 13.0+.

**2. cuCtxCreate API Change (pycuda)**
- CUDA 13.0 changed `cuCtxCreate` from 3 to 4 arguments
- pycuda 2022.2 (current default) uses the old signature and fails to compile
- pycuda 2025.1.2 (D83501913) includes the CUDA 13.0 fix

**Fix:** Added CUDA 13.0 constraint to pycuda alias to auto-select pycuda 2025.1.2.

**NCCL Compatibility Note:**
- Current stable NCCL (2.25) is NOT compatible with CUDA 13.0 (`cudaTypedefs.h` removed)
- NCCL 2.27+ works with CUDA 13.0 and will become stable in early January 2026 (per HPC Comms team)
- Until then, CUDA 13.0 builds require `-c hpc_comms.use_nccl=2.27`

References:
- GitHub issue: https://github.com/facebookresearch/pytorch3d/issues/2011
- NVIDIA blog: https://developer.nvidia.com/blog/cuda-c-compiler-updates-impacting-elf-visibility-and-linkage/
- FBGEMM_GPU fix: D86474263
- pycuda 2025.1.2 buckification: D83501913

Reviewed By: bottler

Differential Revision: D88816596

fbshipit-source-id: 1ba666dab8c0e06d1286b8d5bc5d84cfc55c86e6
2025-12-17 10:02:10 -08:00

197 lines
6.9 KiB
Python
Executable File

#!/usr/bin/env python
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import glob
import os
import runpy
import sys
import warnings
from typing import List, Optional
import torch
from setuptools import find_packages, setup
from torch.utils.cpp_extension import CppExtension, CUDA_HOME, CUDAExtension
def get_existing_ccbin(nvcc_args: List[str]) -> Optional[str]:
"""
Given a list of nvcc arguments, return the compiler if specified.
Note from CUDA doc: Single value options and list options must have
arguments, which must follow the name of the option itself by either
one of more spaces or an equals character.
"""
last_arg = None
for arg in reversed(nvcc_args):
if arg == "-ccbin":
return last_arg
if arg.startswith("-ccbin="):
return arg[7:]
last_arg = arg
return None
def get_extensions():
no_extension = os.getenv("PYTORCH3D_NO_EXTENSION", "0") == "1"
if no_extension:
msg = "SKIPPING EXTENSION BUILD. PYTORCH3D WILL NOT WORK!"
print(msg, file=sys.stderr)
warnings.warn(msg)
return []
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++17"]}
define_macros = []
include_dirs = [extensions_dir]
force_cuda = os.getenv("FORCE_CUDA", "0") == "1"
force_no_cuda = os.getenv("PYTORCH3D_FORCE_NO_CUDA", "0") == "1"
if (
not force_no_cuda and torch.cuda.is_available() and CUDA_HOME is not None
) or force_cuda:
extension = CUDAExtension
sources += source_cuda
define_macros += [("WITH_CUDA", None)]
# Thrust is only used for its tuple objects.
# With CUDA 11.0 we can't use the cudatoolkit's version of cub.
# We take the risk that CUB and Thrust are incompatible, because
# we aren't using parts of Thrust which actually use CUB.
define_macros += [("THRUST_IGNORE_CUB_VERSION_CHECK", None)]
cub_home = os.environ.get("CUB_HOME", None)
nvcc_args = [
"-DCUDA_HAS_FP16=1",
"-D__CUDA_NO_HALF_OPERATORS__",
"-D__CUDA_NO_HALF_CONVERSIONS__",
"-D__CUDA_NO_HALF2_OPERATORS__",
]
if os.name != "nt":
nvcc_args.append("-std=c++17")
# CUDA 13.0+ compatibility flags for pulsar.
# Starting with CUDA 13, __global__ function visibility changed.
# See: https://developer.nvidia.com/blog/
# cuda-c-compiler-updates-impacting-elf-visibility-and-linkage/
cuda_version = torch.version.cuda
if cuda_version is not None:
major = int(cuda_version.split(".")[0])
if major >= 13:
nvcc_args.extend(
[
"--device-entity-has-hidden-visibility=false",
"-static-global-template-stub=false",
]
)
if cub_home is None:
prefix = os.environ.get("CONDA_PREFIX", None)
if prefix is not None and os.path.isdir(prefix + "/include/cub"):
cub_home = prefix + "/include"
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:
include_dirs.append(os.path.realpath(cub_home).replace("\\ ", " "))
nvcc_flags_env = os.getenv("NVCC_FLAGS", "")
if nvcc_flags_env != "":
nvcc_args.extend(nvcc_flags_env.split(" "))
# This is needed for pytorch 1.6 and earlier. See e.g.
# https://github.com/facebookresearch/pytorch3d/issues/436
# It is harmless after https://github.com/pytorch/pytorch/pull/47404 .
# But it can be problematic in torch 1.7.0 and 1.7.1
if torch.__version__[:4] != "1.7.":
CC = os.environ.get("CC", None)
if CC is not None:
existing_CC = get_existing_ccbin(nvcc_args)
if existing_CC is None:
CC_arg = "-ccbin={}".format(CC)
nvcc_args.append(CC_arg)
elif existing_CC != CC:
msg = f"Inconsistent ccbins: {CC} and {existing_CC}"
raise ValueError(msg)
extra_compile_args["nvcc"] = nvcc_args
sources = [os.path.join(extensions_dir, s) for s in sources]
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__(*args, use_ninja=False, **kwargs)
else:
BuildExtension = torch.utils.cpp_extension.BuildExtension
trainer = "pytorch3d.implicitron_trainer"
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", "tests.*", "docs.*", "projects.*")
)
+ [trainer],
package_dir={trainer: "projects/implicitron_trainer"},
install_requires=["iopath"],
extras_require={
"all": ["matplotlib", "tqdm>4.29.0", "imageio", "ipywidgets"],
"dev": ["flake8", "usort"],
"implicitron": [
"hydra-core>=1.1",
"visdom",
"lpips",
"tqdm>4.29.0",
"matplotlib",
"accelerate",
"sqlalchemy>=2.0",
],
},
entry_points={
"console_scripts": [
f"pytorch3d_implicitron_runner={trainer}.experiment:experiment",
f"pytorch3d_implicitron_visualizer={trainer}.visualize_reconstruction:main",
]
},
ext_modules=get_extensions(),
cmdclass={"build_ext": BuildExtension},
package_data={
"": ["*.json"],
},
)