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setup.py
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import os
import subprocess
import sys
import torch
from setuptools import setup, find_packages
from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CUDA_HOME
# ninja build does not work unless include_dirs are abs path
this_dir = os.path.dirname(os.path.abspath(__file__))
build_cuda_ext = True
if '--no_cuda_ext' in sys.argv:
sys.argv.remove('--no_cuda_ext')
build_cuda_ext = False
def get_cuda_bare_metal_version(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]
return raw_output, bare_metal_major, bare_metal_minor
def check_cuda_torch_binary_vs_bare_metal(cuda_dir):
raw_output, bare_metal_major, bare_metal_minor = get_cuda_bare_metal_version(cuda_dir)
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).")
def append_nvcc_threads(nvcc_extra_args):
_, bare_metal_major, bare_metal_minor = get_cuda_bare_metal_version(CUDA_HOME)
if int(bare_metal_major) >= 11 and int(bare_metal_minor) >= 2:
return nvcc_extra_args + ["--threads", "4"]
return nvcc_extra_args
def fetch_requirements(path):
with open(path, 'r') as fd:
return [r.strip() for r in fd.readlines()]
if not torch.cuda.is_available():
# https://github.com/NVIDIA/apex/issues/486
# Extension builds after https://github.com/pytorch/pytorch/pull/23408 attempt to query torch.cuda.get_device_capability(),
# which will fail if you are compiling in an environment without visible GPUs (e.g. during an nvidia-docker build command).
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'
'By default, Colossal-AI will cross-compile for Pascal (compute capabilities 6.0, 6.1, 6.2),\n'
'Volta (compute capability 7.0), Turing (compute capability 7.5),\n'
'and, if the CUDA version is >= 11.0, Ampere (compute capability 8.0).\n'
'If you wish to cross-compile for a single specific architecture,\n'
'export TORCH_CUDA_ARCH_LIST="compute capability" before running setup.py.\n')
if os.environ.get("TORCH_CUDA_ARCH_LIST", None) is None:
_, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME)
if int(bare_metal_major) == 11:
os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5;8.0"
else:
os.environ["TORCH_CUDA_ARCH_LIST"] = "6.0;6.1;6.2;7.0;7.5"
print("\n\ntorch.__version__ = {}\n\n".format(torch.__version__))
TORCH_MAJOR = int(torch.__version__.split('.')[0])
TORCH_MINOR = int(torch.__version__.split('.')[1])
if TORCH_MAJOR < 1 or (TORCH_MAJOR == 1 and TORCH_MINOR < 8):
raise RuntimeError("Requires Pytorch 1.8 or newer.\n" +
"The latest stable release can be obtained from https://pytorch.org/")
cmdclass = {}
ext_modules = []
# Set up macros for forward/backward compatibility hack around
# https://github.com/pytorch/pytorch/commit/4404762d7dd955383acee92e6f06b48144a0742e
# and
# https://github.com/NVIDIA/apex/issues/456
# https://github.com/pytorch/pytorch/commit/eb7b39e02f7d75c26d8a795ea8c7fd911334da7e#diff-4632522f237f1e4e728cb824300403ac
version_dependent_macros = ['-DVERSION_GE_1_1', '-DVERSION_GE_1_3', '-DVERSION_GE_1_5', '-DUSE_C10D_NCCL']
if build_cuda_ext:
if 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(CUDA_HOME)
def cuda_ext_helper(name, sources, extra_cuda_flags):
return CUDAExtension(name=name,
sources=[os.path.join('energon/kernel/cuda_native/csrc', path) for path in sources],
include_dirs=[os.path.join(
this_dir, 'energon/kernel/cuda_native/csrc/kernels/include'), '/opt/lcsoftware/spack/opt/spack/linux-ubuntu20.04-zen2/gcc-9.3.0/nccl-2.9.6-1-ysovaavjkgjez2fwms4dkvatu5yrxbec/include'],
extra_compile_args={'cxx': ['-O3'] + version_dependent_macros,
'nvcc': append_nvcc_threads(['-O3',
'--use_fast_math'] + version_dependent_macros + extra_cuda_flags)})
cc_flag = ['-gencode', 'arch=compute_70,code=sm_70']
_, bare_metal_major, _ = get_cuda_bare_metal_version(CUDA_HOME)
if int(bare_metal_major) >= 11:
cc_flag.append('-gencode')
cc_flag.append('arch=compute_80,code=sm_80')
extra_cuda_flags = ['-std=c++14',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_HALF2_OPERATORS__',
'-DTHRUST_IGNORE_CUB_VERSION_CHECK'
]
ext_modules.append(cuda_ext_helper('energon_scale_mask',
['scale_mask_softmax_kernel.cu',
'scale_mask_softmax_wrapper.cpp'],
extra_cuda_flags + cc_flag))
ext_modules.append(cuda_ext_helper('energon_layer_norm',
['layer_norm_cuda_kernel.cu', 'layer_norm_cuda.cpp'],
extra_cuda_flags + cc_flag))
ext_modules.append(cuda_ext_helper('energon_transpose_pad',
['transpose_pad_fusion_wrapper.cpp', 'transpose_pad_fusion_kernel.cu'],
extra_cuda_flags + cc_flag))
ext_modules.append(cuda_ext_helper('energon_nccl',
['get_ncclid.cpp'],
extra_cuda_flags + cc_flag))
setup(
name='energon',
version='0.0.1-beta',
packages=find_packages(exclude=('benchmark',
'docker',
'tests',
'docs',
'example',
'tests',
'scripts',
'requirements',
'*.egg-info',)),
description='Large-scale Model Inference',
ext_modules=ext_modules,
cmdclass={'build_ext': BuildExtension} if ext_modules else {},
install_requires=fetch_requirements('requirements.txt'),
entry_points='''
[console_scripts]
energon=energon.cli:typer_click_object
'''
)