def get_cmds():
cmds = versioneer.get_cmdclass()
if not (BUILD_CPP or BUILD_CUDA):
return cmds
cmds.update({"build_ext": BuildExtension.with_options(no_python_abi_suffix=True)})
return cmds
setup_requires = ['pytest-runner']
tests_require = ['pytest', 'pytest-cov', 'scipy']
setup(
name='torch_cluster',
version='1.5.7',
author='Matthias Fey',
author_email='*****@*****.**',
url='https://github.com/rusty1s/pytorch_cluster',
description=('PyTorch Extension Library of Optimized Graph Cluster '
'Algorithms'),
keywords=[
'pytorch',
'geometric-deep-learning',
'graph-neural-networks',
'cluster-algorithms',
],
license='MIT',
python_requires='>=3.6',
install_requires=install_requires,
setup_requires=setup_requires,
tests_require=tests_require,
extras_require={'test': tests_require},
ext_modules=get_extensions() if not BUILD_DOCS else [],
cmdclass={
'build_ext':
BuildExtension.with_options(no_python_abi_suffix=True, use_ninja=False)
},
packages=find_packages(),
)
# Final effective mask is the bitwise OR of each op
BUILD_MASK = (DS_BUILD_LAMB | DS_BUILD_TRANSFORMER | DS_BUILD_SPARSE_ATTN)
install_ops = []
if BUILD_MASK & DS_BUILD_LAMB:
install_ops.append('lamb')
if BUILD_MASK & DS_BUILD_TRANSFORMER:
install_ops.append('transformer')
if BUILD_MASK & DS_BUILD_SPARSE_ATTN:
install_ops.append('sparse-attn')
if len(install_ops) == 0:
print("Building without any cuda/cpp extensions")
print(f'BUILD_MASK={BUILD_MASK}, install_ops={install_ops}')
cmdclass = {}
cmdclass['build_ext'] = BuildExtension.with_options(use_ninja=False)
TORCH_MAJOR = int(torch.__version__.split('.')[0])
TORCH_MINOR = int(torch.__version__.split('.')[1])
if not torch.cuda.is_available():
# Fix to allow docker buils, similar to https://github.com/NVIDIA/apex/issues/486
print(
"[WARNING] Torch did not find cuda available, if cross-compling or running with cpu only "
"you can ignore this message. Adding compute capability for Pascal, Volta, and Turing "
"(compute capabilities 6.0, 6.1, 6.2)")
if os.environ.get("TORCH_CUDA_ARCH_LIST", None) is None:
os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5"
# Fix from apex that might be relevant for us as well, related to https://github.com/NVIDIA/apex/issues/456
version_ge_1_1 = []
# It's an old-style class in Python 2.7...
distutils.command.clean.clean.run(self)
setuptools.setup(
name=package_name,
version=package_version,
author="Christian Puhrsch",
author_email="*****@*****.**",
description="NestedTensors for PyTorch",
long_description=readme,
long_description_content_type="text/markdown",
url="https://github.com/pytorch/nestedtensor",
packages=setuptools.find_packages(),
classifiers=[
"Programming Language :: Python :: 3",
"Operating System :: OS Independent",
],
zip_safe=True,
cmdclass={
"clean":
clean,
"build_ext":
BuildExtension.with_options(
use_ninja=os.environ.get("NT_USE_NINJA", False)),
},
install_requires=requirements,
ext_modules=get_extensions(),
)
'nvcc': [
'-std=c++14', '--expt-extended-lambda',
'--use_fast_math', '-Xcompiler', '-Wall',
'-gencode=arch=compute_60,code=sm_60',
'-gencode=arch=compute_61,code=sm_61',
'-gencode=arch=compute_70,code=sm_70',
'-gencode=arch=compute_72,code=sm_72',
'-gencode=arch=compute_75,code=sm_75',
'-gencode=arch=compute_75,code=compute_75'
],
},
library_dirs=['/usr/local/lib/'],
libraries=[
'nvinfer', 'nvinfer_plugin', 'nvonnxparser',
'opencv_core', 'opencv_highgui', 'opencv_imgproc',
'opencv_imgcodecs'
])
],
cmdclass={
'build_ext': BuildExtension.with_options(no_python_abi_suffix=True)
},
install_requires=[
'torch>=1.0.0a0',
#'torchvision',
'apex @ git+https://github.com/NVIDIA/apex',
'pycocotools @ git+https://github.com/nvidia/cocoapi.git#subdirectory=PythonAPI',
'pillow==6.2.2',
'requests',
],
entry_points={'console_scripts': ['retinanet=retinanet.main:main']})
import torch
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
cxx_args = ['-std=c++14']
nvcc_args = [
#'-gencode', 'arch=compute_50,code=sm_50',
#'-gencode', 'arch=compute_52,code=sm_52',
'-gencode',
'arch=compute_60,code=sm_60',
# '-gencode', 'arch=compute_61,code=sm_61',
'-gencode',
'arch=compute_75,code=sm_75',
'-gencode',
'arch=compute_75,code=compute_75'
]
setup(name='local_attn_reshape_cuda',
ext_modules=[
CUDAExtension(
'local_attn_reshape_cuda',
['local_attn_reshape_cuda.cc', 'local_attn_reshape_kernel.cu'],
extra_compile_args={
'cxx': cxx_args,
'nvcc': nvcc_args
})
],
cmdclass={'build_ext': BuildExtension.with_options(use_ninja=False)})
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CppExtension
setup(
name="warp_perspective",
ext_modules=[
CppExtension(
"warp_perspective",
["example_app/warp_perspective/op.cpp"],
libraries=["opencv_core", "opencv_imgproc"],
)
],
cmdclass={"build_ext": BuildExtension.with_options(no_python_abi_suffix=True)},
)
),
]
# Python interface
setup(
name="MinkowskiEngine",
version=find_version("MinkowskiEngine", "__init__.py"),
install_requires=["torch", "numpy"],
packages=[
"MinkowskiEngine", "MinkowskiEngine.utils", "MinkowskiEngine.modules"
],
package_dir={"MinkowskiEngine": "./MinkowskiEngine"},
ext_modules=ext_modules,
include_dirs=[str(SRC_PATH),
str(SRC_PATH / "3rdparty"), *include_dirs],
cmdclass={"build_ext": BuildExtension.with_options(use_ninja=True)},
author="Christopher Choy",
author_email="*****@*****.**",
description="a convolutional neural network library for sparse tensors",
long_description=read("README.md"),
long_description_content_type="text/markdown",
url="https://github.com/NVIDIA/MinkowskiEngine",
keywords=[
"pytorch",
"Minkowski Engine",
"Sparse Tensor",
"Convolutional Neural Networks",
"3D Vision",
"Deep Learning",
],
zip_safe=False,
]
if torch.cuda.is_available() and (CUDA_HOME is not None
or ROCM_HOME is not None):
extension = CUDAExtension('torch_test_cpp_extension.cuda', [
'cuda_extension.cpp',
'cuda_extension_kernel.cu',
'cuda_extension_kernel2.cu',
],
extra_compile_args={
'cxx': CXX_FLAGS,
'nvcc': ['-O2']
})
ext_modules.append(extension)
if torch.cuda.is_available() and (CUDA_HOME is not None
or ROCM_HOME is not None):
extension = CUDAExtension('torch_test_cpp_extension.torch_library',
['torch_library.cu'],
extra_compile_args={
'cxx': CXX_FLAGS,
'nvcc': ['-O2']
})
ext_modules.append(extension)
setup(name='torch_test_cpp_extension',
packages=['torch_test_cpp_extension'],
ext_modules=ext_modules,
include_dirs='self_compiler_include_dirs_test',
cmdclass={'build_ext': BuildExtension.with_options(use_ninja=USE_NINJA)})
# It's an old-style class in Python 2.7...
distutils.command.clean.clean.run(self)
setuptools.setup(
name=package_name,
version=version,
author="Christian Puhrsch",
author_email="*****@*****.**",
description="NestedTensors for PyTorch",
long_description=readme,
long_description_content_type="text/markdown",
url="https://github.com/pytorch/nestedtensor",
packages=setuptools.find_packages(),
classifiers=[
"Programming Language :: Python :: 3",
"Operating System :: OS Independent",
],
zip_safe=True,
cmdclass={
"clean":
clean,
"build_ext":
BuildExtension.with_options(no_python_abi_suffix=True,
use_ninja=os.environ.get(
"USE_NINJA", False)),
},
install_requires=requirements,
ext_modules=get_extensions(),
)
class FBGEMM_GPU_BuildExtension(
BuildExtension.with_options(no_python_abi_suffix=True)):
def build_extension(self, ext):
generate_jinja_files()
super().build_extension(ext)
from setuptools import find_packages
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
setup(
name='fused_lamb',
description="Fused LAMB Optimizer for PyTorch native AMP training",
packages=find_packages(exclude=('test', )), # NOQA
ext_modules=[
CUDAExtension(name='fused_lamb_CUDA',
sources=[
'csrc/frontend.cpp',
'csrc/multi_tensor_l2norm_kernel.cu',
'csrc/multi_tensor_lamb.cu',
],
extra_compile_args={
'nvcc': [
'-lineinfo',
'-O3',
'--use_fast_math',
],
}),
],
cmdclass={
'build_ext': BuildExtension.with_options(use_ninja=True),
},
)
