def ext_modules():
extensions = [
cpp_extension.CppExtension(
"torchsort.isotonic_cpu",
sources=["torchsort/isotonic_cpu.cpp"],
extra_compile_args=compile_args(),
),
]
if cuda_toolkit_available():
extensions.append(
cpp_extension.CUDAExtension(
"torchsort.isotonic_cuda",
sources=["torchsort/isotonic_cuda.cu"],
))
return extensions
def get_extensions():
# This code originally offered non-CUDA compilation... this seemed to be a
# lie though as crucial methods like "modulated_deform_conv" are currently
# unimplemented for CPU. Instead, we bite the bullet and make CUDA an
# explicit requirement for this package. It matches the typical use-case at
# the end of the day.
root = os.path.join('fcos', 'core', 'csrc')
return [
tcpp.CUDAExtension("fcos.core._C",
[glob(os.path.join(root, '*.cpp'))[0]] +
glob(os.path.join(root, 'cpu', '*.cpp')) +
glob(os.path.join(root, 'cuda', '*.cu')),
include_dirs=[root],
define_macros=[("WITH_CUDA", None)],
extra_compile_args={
"cxx": [],
"nvcc": [
"-DCUDA_HAS_FP16=1",
"-D__CUDA_NO_HALF_OPERATORS__",
"-D__CUDA_NO_HALF_CONVERSIONS__",
"-D__CUDA_NO_HALF2_OPERATORS__",
]
})
]
from setuptools import setup
from torch.utils import cpp_extension
setup(name='rle',
description="a package used for compress sparse tensor",
packages=["rle"],
package_data={"rle": ["__init__.py"]},
ext_modules=[
cpp_extension.CUDAExtension('rle_cuda', [
'rle_cuda.cpp',
'rle_cuda_kernel.cu',
]),
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
from setuptools import setup, Extension
from torch.utils import cpp_extension
setup(name='lltm_cpp',
ext_modules=[
cpp_extension.CppExtension('lltm_cpp', ['./models/ops/lltm.cpp'])
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
setup(name='lltm_cuda',
ext_modules=[
cpp_extension.CUDAExtension('lltm_cuda', [
'./models/ops/lltm_cuda.cpp',
'./models/ops/lltm_cuda_kernel.cu',
])
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
plugin_include_dirs = [
"{}/include/".format(ucc_plugin_dir), "{}/include/".format(ucx_home),
"{}/include/".format(ucc_home)
]
plugin_library_dirs = ["{}/lib/".format(ucx_home), "{}/lib/".format(ucc_home)]
plugin_libraries = ["ucp", "uct", "ucm", "ucs", "ucc"]
with_cuda = os.environ.get("WITH_CUDA")
if with_cuda is None or with_cuda == "no":
print("CUDA support is disabled")
module = cpp_extension.CppExtension(name="torch_ucc",
sources=plugin_sources,
include_dirs=plugin_include_dirs,
library_dirs=plugin_library_dirs,
libraries=plugin_libraries,
extra_compile_args=plugin_compile_args)
else:
print("CUDA support is enabled")
plugin_compile_args.append("-DUSE_CUDA")
module = cpp_extension.CUDAExtension(
name="torch_ucc",
sources=plugin_sources,
include_dirs=plugin_include_dirs,
library_dirs=plugin_library_dirs,
libraries=plugin_libraries,
extra_compile_args=plugin_compile_args)
setup(name="torch-ucc",
version="1.0.0",
ext_modules=[module],
cmdclass={'build_ext': cpp_extension.BuildExtension})
import fileinput
import os
import sys
from setuptools import setup
from torch.utils import cpp_extension
filenames = [
os.path.join(os.path.dirname(__file__), "fused_ops_frontend.cpp"),
os.path.join(os.path.dirname(__file__), "multi_tensor_adam.cu"),
os.path.join(os.path.dirname(__file__), "multi_tensor_scale_kernel.cu"),
os.path.join(os.path.dirname(__file__), "multi_tensor_axpby_kernel.cu"),
]
use_rocm = True if os.environ["ONNXRUNTIME_ROCM_VERSION"] else False
extra_compile_args = {"cxx": ["-O3"]}
if not use_rocm:
extra_compile_args.update(
{"nvcc": ["-lineinfo", "-O3", "--use_fast_math"]})
setup(
name="fused_ops",
ext_modules=[
cpp_extension.CUDAExtension(name="fused_ops",
sources=filenames,
extra_compile_args=extra_compile_args)
],
cmdclass={"build_ext": cpp_extension.BuildExtension},
)
rmtree(path)
ext_modules = [
cpp_extension.CUDAExtension(
'trtorch._C', [
'trtorch/csrc/trtorch_py.cpp',
'trtorch/csrc/tensorrt_backend.cpp',
'trtorch/csrc/tensorrt_classes.cpp',
'trtorch/csrc/register_tensorrt_classes.cpp',
],
library_dirs=[(dir_path + '/trtorch/lib/'), "/opt/conda/lib/python3.6/config-3.6m-x86_64-linux-gnu"],
libraries=["trtorch"],
include_dirs=[
dir_path + "trtorch/csrc",
dir_path + "/../",
dir_path + "/../bazel-TRTorch/external/tensorrt/include",
],
extra_compile_args=[
"-Wno-deprecated",
"-Wno-deprecated-declarations",
] + (["-D_GLIBCXX_USE_CXX11_ABI=1"] if CXX11_ABI else ["-D_GLIBCXX_USE_CXX11_ABI=0"]),
extra_link_args=[
"-Wno-deprecated", "-Wno-deprecated-declarations", "-Wl,--no-as-needed", "-ltrtorch",
"-Wl,-rpath,$ORIGIN/lib", "-lpthread", "-ldl", "-lutil", "-lrt", "-lm", "-Xlinker", "-export-dynamic"
] + (["-D_GLIBCXX_USE_CXX11_ABI=1"] if CXX11_ABI else ["-D_GLIBCXX_USE_CXX11_ABI=0"]),
undef_macros=["NDEBUG"])
]
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
import os
from setuptools import setup, Extension
from torch.utils import cpp_extension
# library_dirs should point to the libtrtorch.so, include_dirs should point to the dir that include the headers
# 1) download the latest package from https://github.com/NVIDIA/TRTorch/releases/
# 2) Extract the file from downloaded package, we will get the "trtorch" directory
# 3) Set trtorch_path to that directory
trtorch_path = <PATH TO TRTORCH>
ext_modules = [
cpp_extension.CUDAExtension('elu_converter', ['./csrc/elu_converter.cpp'],
library_dirs=[(trtorch_path + "/lib/")],
libraries=["trtorch"],
include_dirs=[trtorch_path + "/include/trtorch/"])
]
setup(
name='elu_converter',
ext_modules=ext_modules,
cmdclass={'build_ext': cpp_extension.BuildExtension},
)
base_path = os.path.dirname(os.path.realpath(__file__))
if 'Windows' in platform():
CUDA_HOME = os.environ.get('CUDA_HOME', os.environ.get('CUDA_PATH'))
extra_args = []
else:
CUDA_HOME = os.environ.get('CUDA_HOME', '/usr/local/cuda')
extra_args = ['-Wno-sign-compare']
with open(f'frameworks/pytorch/_version.py', 'wt') as f:
f.write(f'__version__ = "{VERSION}"')
extension = cpp_extension.CUDAExtension(
'haste_pytorch_lib',
sources=glob('frameworks/pytorch/*.cc'),
extra_compile_args=extra_args,
include_dirs=[
os.path.join(base_path, 'lib'),
os.path.join(CUDA_HOME, 'include')
],
libraries=['haste'],
library_dirs=['.'])
setup(name='haste_pytorch',
version=VERSION,
description=DESCRIPTION,
long_description=open('README.md', 'r', encoding='utf-8').read(),
long_description_content_type='text/markdown',
author=AUTHOR,
author_email=AUTHOR_EMAIL,
url=URL,
license=LICENSE,
keywords='pytorch machine learning rnn lstm gru custom op',
rmtree(path)
ext_modules = [
cpp_extension.CUDAExtension('trtorch._C',
['trtorch/csrc/trtorch_py.cpp'],
library_dirs=[
dir_path + '/trtorch/lib/libtrtorch.so',
dir_path + '/trtorch/lib/'
],
libraries=[
"trtorch"
],
include_dirs=[
dir_path + "/../",
dir_path + "/../bazel-TRTorch/external/tensorrt/include",
],
extra_compile_args=[
"-D_GLIBCXX_USE_CXX11_ABI=0",
"-Wno-deprecated-declaration",
],
extra_link_args=[
"-D_GLIBCXX_USE_CXX11_ABI=0"
"-Wl,--no-as-needed",
"-ltrtorch",
"-Wl,-rpath,$ORIGIN/lib"
],
undef_macros=[ "NDEBUG" ]
)
]
with open("README.md", "r") as fh:
import torch
from setuptools import setup
import torch.utils.cpp_extension as cpp
# In any case, include the CPU version
modules = [
cpp.CppExtension('torchsearchsorted.cpu',
['torchsearchsorted/cpu/searchsorted_cpu_wrapper.cpp'])
]
# if CUDA is available, add the cuda extension
if torch.cuda.is_available():
modules += [
cpp.CUDAExtension('torchsearchsorted.cuda', [
'torchsearchsorted/cuda/searchsorted_cuda_wrapper.cpp',
'torchsearchsorted/cuda/searchsorted_cuda_kernel.cu'
])
]
# Now proceed to setup
setup(name='torchsearchsorted',
version='1.0',
description='A searchsorted implementation for pytorch',
keywords='searchsorted',
author='Antoine Liutkus',
author_email='*****@*****.**',
packages=['torchsearchsorted'],
ext_modules=modules,
cmdclass={'build_ext': cpp.BuildExtension})
from setuptools import setup, Extension
from torch.utils import cpp_extension
setup(name='double_ext',
ext_modules=[
cpp_extension.CUDAExtension('double_ext', ['double_ext.cpp'],
libraries=['double_kernel'])
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
"""
Created at 07.11.19 19:12
@author: gregor
"""
from setuptools import setup
from torch.utils import cpp_extension
setup(name='sandbox_cuda',
ext_modules=[
cpp_extension.CUDAExtension(
'sandbox', ['src/sandbox.cpp', 'src/sandbox_cuda.cu'])
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
"""
Created at 07.11.19 19:12
@author: gregor
"""
import os, sys, site
from pathlib import Path
# recognise newly installed packages in path
site.main()
from setuptools import setup
from torch.utils import cpp_extension
dir_ = Path(os.path.dirname(sys.argv[0]))
setup(name='RoIAlign extension 2D',
ext_modules=[cpp_extension.CUDAExtension('roi_al_extension', [str(dir_/'src/RoIAlign_interface.cpp'),
str(dir_/'src/RoIAlign_cuda.cu')])],
cmdclass={'build_ext': cpp_extension.BuildExtension}
)
setup(name='RoIAlign extension 3D',
ext_modules=[cpp_extension.CUDAExtension('roi_al_extension_3d', [str(dir_/'src/RoIAlign_interface_3d.cpp'),
str(dir_/'src/RoIAlign_cuda_3d.cu')])],
cmdclass={'build_ext': cpp_extension.BuildExtension}
)
from setuptools import setup
from torch.utils import cpp_extension
import os
import glob
ext_modules = [
cpp_extension.CppExtension(
"splatting.cpu",
["cpp/splatting.cpp"],
),
]
cublas_include_paths = glob.glob("/usr/local/**/cublas_v2.h", recursive=True)
if len(cublas_include_paths) > 0:
ext_modules.append(
cpp_extension.CUDAExtension(
"splatting.cuda",
["cuda/splatting_cuda.cpp", "cuda/splatting.cu"],
include_dirs=[os.path.dirname(cublas_include_paths[0])],
), )
setup(
name="splatting",
ext_modules=ext_modules,
cmdclass={"build_ext": cpp_extension.BuildExtension},
install_requires=["torch"],
extras_require={"dev": ["pytest", "pytest-cov",
"pre-commit"]}, # pip install -e '.[dev]'
)
from setuptools import setup, Extension
from torch.utils import cpp_extension
# setup(name='dp_cpp',
# ext_modules=[cpp_extension.CppExtension('lltm_cpp', ['lltm.cpp'])],
# cmdclass={'build_ext': cpp_extension.BuildExtension})
setup(
name='dp_cuda',
ext_modules=[
cpp_extension.CUDAExtension('dp_cuda', [
'dp_cuda.cpp',
'dp_cuda_kernel.cu',
])
],
cmdclass={
'build_ext': cpp_extension.BuildExtension
})
setup(
name='dp_ne_cuda',
ext_modules=[
cpp_extension.CUDAExtension('dp_ne_cuda', [
'dp_ne_cuda.cpp',
'dp_ne_cuda_kernel.cu',
])
],
cmdclass={
'build_ext': cpp_extension.BuildExtension
})
# setup(
# name='dp_ne_rank1_cuda',
from setuptools import setup, Extension
from torch.utils import cpp_extension
setup(name='smear_cuda',
ext_modules=[
cpp_extension.CUDAExtension(
'smear_cuda', ['smear_cuda.cpp', 'smear_cuda_kernel.cu'])
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
from setuptools import setup, Extension, find_packages
from torch.utils import cpp_extension
'''
python setup.py install
usage: import torch first, then import this module
'''
setup(name='pytorch_loss',
ext_modules=[
cpp_extension.CUDAExtension('focal_cpp', [
'csrc/focal_kernel.cu',
]),
cpp_extension.CUDAExtension('mish_cpp', ['csrc/mish_kernel.cu']),
cpp_extension.CUDAExtension('swish_cpp', ['csrc/swish_kernel.cu']),
cpp_extension.CUDAExtension('soft_dice_cpp',
['csrc/soft_dice_kernel_v2.cu']),
cpp_extension.CUDAExtension('lsr_cpp', ['csrc/lsr_kernel.cu']),
cpp_extension.CUDAExtension('large_margin_cpp',
['csrc/large_margin_kernel.cu']),
cpp_extension.CUDAExtension('ohem_cpp',
['csrc/ohem_label_kernel.cu']),
cpp_extension.CUDAExtension('one_hot_cpp',
['csrc/one_hot_kernel.cu']),
cpp_extension.CUDAExtension('lovasz_softmax_cpp',
['csrc/lovasz_softmax.cu']),
cpp_extension.CUDAExtension('taylor_softmax_cpp',
['csrc/taylor_softmax.cu']),
],
cmdclass={'build_ext': cpp_extension.BuildExtension},
packages=find_packages())
from setuptools import setup, Extension
from torch.utils import cpp_extension
setup(name='rel_to_abs_index_cuda',
ext_modules=[
cpp_extension.CUDAExtension(
'rel_to_abs_index_cuda',
['rel_to_abs_index_cuda.cpp', 'rel_to_abs_index_cuda_kernel.cu'])
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
from setuptools import setup, Extension, find_packages
from torch.utils import cpp_extension
setup(
name='quant',
ext_modules=[
cpp_extension.CUDAExtension('quant.cpp_extension.calc_quant_bin',
['quant/cpp_extension/calc_quant_bin.cc']),
],
cmdclass={'build_ext': cpp_extension.BuildExtension},
packages=find_packages())
from setuptools import setup, Extension
from torch.utils import cpp_extension
import os
module_path = os.path.dirname(__file__)
setup(name='op_cpp',
ext_modules=[
cpp_extension.CUDAExtension(
name="fused",
sources=["fused_bias_act.cpp", "fused_bias_act_kernel.cu"],
include_dirs=cpp_extension.include_paths(),
),
cpp_extension.CUDAExtension(
name="upfirdn2d",
sources=["upfirdn2d.cpp", "upfirdn2d_kernel.cu"],
include_dirs=cpp_extension.include_paths(),
),
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
current_dir = os.path.dirname(os.path.abspath(__file__))
cuda_sources = glob.glob(os.path.join(current_dir, 'csrc', 'core', '*.cu'))
cpp_sources = glob.glob(os.path.join(current_dir, 'csrc', 'op', '*.cpp'))
py11_sources = glob.glob(os.path.join(current_dir, 'csrc', 'py11', '*.cpp'))
sources = cuda_sources + cpp_sources + py11_sources
cuda_include_paths = cpp_extension.include_paths(cuda=True)
self_include_paths = [os.path.join(current_dir, 'csrc')]
include_paths = cuda_include_paths + self_include_paths
setup(name='EET',
version=__version__,
package_dir={"": "python"},
packages=find_packages("python"),
ext_modules=[
cpp_extension.CUDAExtension(name='EET',
sources=sources,
include_dirs=include_paths,
extra_compile_args={
'cxx': ['-g'],
'nvcc': [
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_HALF2_OPERATORS__'
]
},
define_macros=[('VERSION_INFO',
__version__)])
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
import torch.cuda
from torch.utils import cpp_extension
sourceFiles = ['hingetree.cpp']
extraCflags = ['-O2']
extraCudaFlags = ['-O2']
if torch.cuda.is_available():
sourceFiles.append('hingetree_gpu.cu')
extraCflags.append('-DWITH_CUDA=1')
setup(name='hingetree_cpp',
ext_modules=[
cpp_extension.CUDAExtension(name='hingetree_cpp',
sources=sourceFiles,
extra_compile_args={
'cxx': extraCflags,
'nvcc': extraCudaFlags
})
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
else:
setup(name='hingetree_cpp',
ext_modules=[
cpp_extension.CppExtension(name='hingetree_cpp',
sources=sourceFiles,
extra_compile_args={
'cxx': extraCflags,
'nvcc': extraCudaFlags
})
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
"""
Created at 07.11.19 19:12
@author: gregor
"""
import os, sys, site
from pathlib import Path
# recognise newly installed packages in path
site.main()
from setuptools import setup
from torch.utils import cpp_extension
dir_ = Path(os.path.dirname(sys.argv[0]))
setup(name='nms_extension',
ext_modules=[
cpp_extension.CUDAExtension(
'nms_extension',
[str(dir_ / 'src/nms_interface.cpp'),
str(dir_ / 'src/nms.cu')])
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
import fileinput
import os
import sys
from setuptools import setup
from torch.utils import cpp_extension
# TODO: Implement a cleaner way to auto-generate torch_gpu_allocator.cc
use_rocm = True if os.environ["ONNXRUNTIME_ROCM_VERSION"] else False
gpu_identifier = "hip" if use_rocm else "cuda"
gpu_allocator_header = "HIPCachingAllocator" if use_rocm else "CUDACachingAllocator"
filename = os.path.join(os.path.dirname(__file__), "torch_gpu_allocator.cc")
with fileinput.FileInput(filename, inplace=True) as file:
for line in file:
if "___gpu_identifier___" in line:
line = line.replace("___gpu_identifier___", gpu_identifier)
if "___gpu_allocator_header___" in line:
line = line.replace("___gpu_allocator_header___",
gpu_allocator_header)
sys.stdout.write(line)
setup(
name="torch_gpu_allocator",
ext_modules=[
cpp_extension.CUDAExtension(name="torch_gpu_allocator",
sources=[filename])
],
cmdclass={"build_ext": cpp_extension.BuildExtension},
)
''' File Created: Mon Mar 02 2020 Author: Peng YUN ([email protected]) Copyright 2018-2020 Peng YUN, RAM-Lab, HKUST ''' from setuptools import setup, Extension from torch.utils import cpp_extension setup(name='iou_cpp', ext_modules=[cpp_extension.CppExtension('iou_cpp', ['iou.cpp'])], cmdclass={'build_ext': cpp_extension.BuildExtension}) setup(name='boxop_cpp', ext_modules=[cpp_extension.CppExtension('boxop_cpp', ['boxop.cpp'])], cmdclass={'build_ext': cpp_extension.BuildExtension}) setup(name='iou_cuda', ext_modules=[ cpp_extension.CUDAExtension('iou_cuda', ['iou_cuda.cpp', 'iou_cuda_kernel.cu']) ], cmdclass={'build_ext': cpp_extension.BuildExtension}) setup(name='boxop_cuda', ext_modules=[ cpp_extension.CUDAExtension( 'boxop_cuda', ['boxop_cuda.cpp', 'boxop_cuda_kernel.cu']) ], cmdclass={'build_ext': cpp_extension.BuildExtension})
from setuptools import setup, Extension
from torch.utils import cpp_extension
# setup(name='dp_cpp',
# ext_modules=[cpp_extension.CppExtension('lltm_cpp', ['lltm.cpp'])],
# cmdclass={'build_ext': cpp_extension.BuildExtension})
setup(name='inplace_abn',
ext_modules=[
cpp_extension.CUDAExtension('inplace_abn', [
'inplace_abn.cpp',
'inplace_abn_cpu.cpp',
'inplace_abn_cuda.cu',
],
extra_compile_args={
'nvcc': ["--expt-extended-lambda"],
'cxx': ["-O3"]
})
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
from setuptools import setup, Extension
from torch.utils import cpp_extension
setup(name='calc_assoc_cuda',
ext_modules=[
cpp_extension.CUDAExtension(
'calc_assoc_cuda',
['calc_assoc_cuda.cpp', 'calc_assoc_cuda_kernel.cu'])
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
from setuptools import setup, Extension
from torch.utils import cpp_extension
'''
python setup.py install
usage: import torch first, then import this module
'''
setup(name='pytorch_loss',
ext_modules=[
cpp_extension.CUDAExtension(
'focal_cpp', ['csrc/focal.cpp', 'csrc/focal_kernel.cu']),
cpp_extension.CUDAExtension('mish_cpp', ['csrc/mish_kernel.cu']),
cpp_extension.CUDAExtension('swish_cpp', ['csrc/swish_kernel.cu']),
cpp_extension.CUDAExtension('soft_dice_cpp',
['csrc/soft_dice_kernel.cu']),
cpp_extension.CUDAExtension('lsr_cpp', ['csrc/lsr_kernel_v2.cu']),
cpp_extension.CUDAExtension('large_margin_cpp',
['csrc/large_margin_kernel.cu']),
cpp_extension.CUDAExtension('ohem_cpp',
['csrc/ohem_label_kernel.cu']),
],
cmdclass={'build_ext': cpp_extension.BuildExtension})
"Removing them to avoid compilation problems.")
os.environ[FLAG] = re.sub(r' -std=[^ ]*', '', os.environ[FLAG])
from setuptools import setup
import torch
from torch.utils import cpp_extension
import glob
ext_modules = [
cpp_extension.CppExtension(
"splatting.cpu",
["cpp/splatting.cpp"],
),
]
if torch.cuda.is_available():
ext_modules.append(
cpp_extension.CUDAExtension(
"splatting.cuda",
["cuda/splatting_cuda.cpp", "cuda/splatting.cu"],
), )
setup(
name="splatting",
ext_modules=ext_modules,
cmdclass={"build_ext": cpp_extension.BuildExtension},
packages=["splatting"],
install_requires=["torch"],
extras_require={"dev": ["pytest", "pytest-cov", "pre-commit"]},
)
