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setup.py
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import torch
from setuptools import setup, find_packages
import subprocess
from pip._internal import main as pipmain
import sys
import warnings
if not torch.cuda.is_available():
print("\nWarning: Torch did not find available GPUs on this system.\n",
"If your intention is to cross-compile, this is not an error.\n")
print("torch.__version__ = ", torch.__version__)
TORCH_MAJOR = int(torch.__version__.split('.')[0])
TORCH_MINOR = int(torch.__version__.split('.')[1])
if TORCH_MAJOR == 0 and TORCH_MINOR < 4:
raise RuntimeError("Apex requires Pytorch 0.4 or newer.\n" +
"The latest stable release can be obtained from https://pytorch.org/")
cmdclass = {}
ext_modules = []
if "--pyprof" in sys.argv:
with open('requirements.txt') as f:
required_packages = f.read().splitlines()
pipmain(["install"] + required_packages)
try:
sys.argv.remove("--pyprof")
except:
pass
else:
warnings.warn("Option --pyprof not specified. Not installing PyProf dependencies!")
if "--cpp_ext" in sys.argv or "--cuda_ext" in sys.argv:
if TORCH_MAJOR == 0:
raise RuntimeError("--cpp_ext requires Pytorch 1.0 or later, "
"found torch.__version__ = {}".format(torch.__version__))
from torch.utils.cpp_extension import BuildExtension
cmdclass['build_ext'] = BuildExtension
if "--cpp_ext" in sys.argv:
from torch.utils.cpp_extension import CppExtension
sys.argv.remove("--cpp_ext")
ext_modules.append(
CppExtension('apex_C',
['csrc/flatten_unflatten.cpp',]))
def check_cuda_torch_binary_vs_bare_metal(cuda_dir):
raw_output = subprocess.check_output([cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True)
output = raw_output.split()
release_idx = output.index("release") + 1
release = output[release_idx].split(".")
bare_metal_major = release[0]
bare_metal_minor = release[1][0]
torch_binary_major = torch.version.cuda.split(".")[0]
torch_binary_minor = torch.version.cuda.split(".")[1]
print("\nCompiling cuda extensions with")
print(raw_output + "from " + cuda_dir + "/bin\n")
if (bare_metal_major != torch_binary_major) or (bare_metal_minor != torch_binary_minor):
raise RuntimeError("Cuda extensions are being compiled with a version of Cuda that does " +
"not match the version used to compile Pytorch binaries. " +
"Pytorch binaries were compiled with Cuda {}.\n".format(torch.version.cuda) +
"In some cases, a minor-version mismatch will not cause later errors: " +
"https://github.com/NVIDIA/apex/pull/323#discussion_r287021798. "
"You can try commenting out this check (at your own risk).")
if "--cuda_ext" in sys.argv:
from torch.utils.cpp_extension import CUDAExtension
sys.argv.remove("--cuda_ext")
if torch.utils.cpp_extension.CUDA_HOME is None:
raise RuntimeError("--cuda_ext was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.")
else:
check_cuda_torch_binary_vs_bare_metal(torch.utils.cpp_extension.CUDA_HOME)
# Set up macros for forward/backward compatibility hack around
# https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e
version_ge_1_1 = []
if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 0):
version_ge_1_1 = ['-DVERSION_GE_1_1']
ext_modules.append(
CUDAExtension(name='amp_C',
sources=['csrc/amp_C_frontend.cpp',
'csrc/multi_tensor_sgd_kernel.cu',
'csrc/multi_tensor_scale_kernel.cu',
'csrc/multi_tensor_axpby_kernel.cu',
'csrc/multi_tensor_l2norm_kernel.cu',
'csrc/multi_tensor_lamb_stage_1.cu',
'csrc/multi_tensor_lamb_stage_2.cu',
'csrc/multi_tensor_adam.cu',
'csrc/multi_tensor_novograd.cu',
'csrc/multi_tensor_lamb.cu'],
extra_compile_args={'cxx': ['-O3'],
'nvcc':['-lineinfo',
'-O3',
# '--resource-usage',
'--use_fast_math']}))
ext_modules.append(
CUDAExtension(name='fused_adam_cuda',
sources=['csrc/fused_adam_cuda.cpp',
'csrc/fused_adam_cuda_kernel.cu'],
extra_compile_args={'cxx': ['-O3',],
'nvcc':['-O3',
'--use_fast_math']}))
ext_modules.append(
CUDAExtension(name='syncbn',
sources=['csrc/syncbn.cpp',
'csrc/welford.cu']))
ext_modules.append(
CUDAExtension(name='fused_layer_norm_cuda',
sources=['csrc/layer_norm_cuda.cpp',
'csrc/layer_norm_cuda_kernel.cu'],
extra_compile_args={'cxx': ['-O3'] + version_ge_1_1,
'nvcc':['-maxrregcount=50',
'-O3',
'--use_fast_math'] + version_ge_1_1}))
if "--bnp" in sys.argv:
from torch.utils.cpp_extension import CUDAExtension
sys.argv.remove("--bnp")
from torch.utils.cpp_extension import BuildExtension
cmdclass['build_ext'] = BuildExtension
if torch.utils.cpp_extension.CUDA_HOME is None:
raise RuntimeError("--bnp was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.")
else:
# Set up macros for forward/backward compatibility hack around
# https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e
version_ge_1_1 = []
if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 0):
version_ge_1_1 = ['-DVERSION_GE_1_1']
ext_modules.append(
CUDAExtension(name='bnp',
sources=['apex/contrib/csrc/groupbn/batch_norm.cu',
'apex/contrib/csrc/groupbn/ipc.cu',
'apex/contrib/csrc/groupbn/interface.cpp',
'apex/contrib/csrc/groupbn/batch_norm_add_relu.cu'],
extra_compile_args={'cxx': [] + version_ge_1_1,
'nvcc':['-DCUDA_HAS_FP16=1',
'-D__CUDA_NO_HALF_OPERATORS__',
'-D__CUDA_NO_HALF_CONVERSIONS__',
'-D__CUDA_NO_HALF2_OPERATORS__',
'-gencode',
'arch=compute_70,code=sm_70'] + version_ge_1_1}))
if "--xentropy" in sys.argv:
from torch.utils.cpp_extension import CUDAExtension
sys.argv.remove("--xentropy")
from torch.utils.cpp_extension import BuildExtension
cmdclass['build_ext'] = BuildExtension
if torch.utils.cpp_extension.CUDA_HOME is None:
raise RuntimeError("--xentropy was requested, but nvcc was not found. Are you sure your environment has nvcc available? If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.")
else:
# Set up macros for forward/backward compatibility hack around
# https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e
version_ge_1_1 = []
if (TORCH_MAJOR > 1) or (TORCH_MAJOR == 1 and TORCH_MINOR > 0):
version_ge_1_1 = ['-DVERSION_GE_1_1']
ext_modules.append(
CUDAExtension(name='xentropy_cuda',
sources=['apex/contrib/csrc/xentropy/interface.cpp',
'apex/contrib/csrc/xentropy/xentropy_kernel.cu'],
include_dirs=['csrc'],
extra_compile_args={'cxx': ['-O3'] + version_ge_1_1,
'nvcc':['-O3'] + version_ge_1_1}))
setup(
name='apex',
version='0.1',
packages=find_packages(exclude=('build',
'csrc',
'include',
'tests',
'dist',
'docs',
'tests',
'examples',
'apex.egg-info',)),
description='PyTorch Extensions written by NVIDIA',
ext_modules=ext_modules,
cmdclass=cmdclass,
)