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setup.py
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setup.py
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#!/usr/bin/env python3 -u
# Copyright (c) DP Technology.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch.utils import cpp_extension
from torch.utils.cpp_extension import CUDAExtension, BuildExtension
import os
import subprocess
import sys
from setuptools import find_packages, setup
DISABLE_CUDA_EXTENSION = True
filtered_args = []
for i, arg in enumerate(sys.argv):
if arg == '--enable-cuda-ext':
DISABLE_CUDA_EXTENSION = False
continue
filtered_args.append(arg)
sys.argv = filtered_args
if sys.version_info < (3, 7):
sys.exit("Sorry, Python >= 3.7 is required for unicore.")
def write_version_py():
with open(os.path.join("unicore", "version.txt")) as f:
version = f.read().strip()
# write version info to unicore/version.py
with open(os.path.join("unicore", "version.py"), "w") as f:
f.write('__version__ = "{}"\n'.format(version))
return version
version = write_version_py()
# # ninja build does not work unless include_dirs are abs path
this_dir = os.path.dirname(os.path.abspath(__file__))
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
if not torch.cuda.is_available() and not DISABLE_CUDA_EXTENSION:
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, it will cross-compile for 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(cpp_extension.CUDA_HOME)
if int(bare_metal_major) == 11:
os.environ["TORCH_CUDA_ARCH_LIST"] = "7.0;7.5;8.0;9.0"
else:
os.environ["TORCH_CUDA_ARCH_LIST"] = "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 not ( (TORCH_MAJOR >= 1 and TORCH_MINOR >= 4)
or (TORCH_MAJOR > 1)
):
raise RuntimeError("Requires Pytorch 1.4 or newer.\n" +
"The latest stable release can be obtained from https://pytorch.org/")
cmdclass = {}
ext_modules = []
extras = {}
if not DISABLE_CUDA_EXTENSION:
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))
cmdclass['build_ext'] = BuildExtension
if torch.utils.cpp_extension.CUDA_HOME is None:
raise RuntimeError("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.")
# check_cuda_torch_binary_vs_bare_metal(torch.utils.cpp_extension.CUDA_HOME)
generator_flag = []
torch_dir = torch.__path__[0]
if os.path.exists(os.path.join(torch_dir, 'include', 'ATen', 'CUDAGenerator.h')):
generator_flag = ['-DOLD_GENERATOR']
ext_modules.append(
CUDAExtension(name='unicore_fused_rounding',
sources=['csrc/rounding/interface.cpp',
'csrc/rounding/fp32_to_bf16.cu'],
include_dirs=[os.path.join(this_dir, 'csrc')],
extra_compile_args={'cxx': ['-O3',] + generator_flag,
'nvcc':['-O3', '--use_fast_math',
'-gencode', 'arch=compute_70,code=sm_70',
'-gencode', 'arch=compute_80,code=sm_80',
'-gencode', 'arch=compute_90,code=sm_90',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_BFLOAT16_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
'--expt-relaxed-constexpr',
'--expt-extended-lambda'] + generator_flag}))
ext_modules.append(
CUDAExtension(name='unicore_fused_multi_tensor',
sources=['csrc/multi_tensor/interface.cpp',
'csrc/multi_tensor/multi_tensor_l2norm_kernel.cu'],
include_dirs=[os.path.join(this_dir, 'csrc')],
extra_compile_args={'cxx': ['-O3'],
'nvcc':['-O3', '--use_fast_math',
'-gencode', 'arch=compute_70,code=sm_70',
'-gencode', 'arch=compute_80,code=sm_80',
'-gencode', 'arch=compute_90,code=sm_90',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_BFLOAT16_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
'--expt-relaxed-constexpr',
'--expt-extended-lambda']
}))
ext_modules.append(
CUDAExtension(name='unicore_fused_adam',
sources=['csrc/adam/interface.cpp',
'csrc/adam/adam_kernel.cu'],
include_dirs=[os.path.join(this_dir, 'csrc')],
extra_compile_args={'cxx': ['-O3'],
'nvcc':['-O3', '--use_fast_math',
'-gencode', 'arch=compute_70,code=sm_70',
'-gencode', 'arch=compute_80,code=sm_80',
'-gencode', 'arch=compute_90,code=sm_90']}))
ext_modules.append(
CUDAExtension(name='unicore_fused_softmax_dropout',
sources=['csrc/softmax_dropout/interface.cpp',
'csrc/softmax_dropout/softmax_dropout_kernel.cu'],
include_dirs=[os.path.join(this_dir, 'csrc')],
extra_compile_args={'cxx': ['-O3',] + generator_flag,
'nvcc':['-O3', '--use_fast_math',
'-gencode', 'arch=compute_70,code=sm_70',
'-gencode', 'arch=compute_80,code=sm_80',
'-gencode', 'arch=compute_90,code=sm_90',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_BFLOAT16_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
'--expt-relaxed-constexpr',
'--expt-extended-lambda'] + generator_flag}))
ext_modules.append(
CUDAExtension(name='unicore_fused_layernorm',
sources=['csrc/layernorm/interface.cpp',
'csrc/layernorm/layernorm.cu'],
include_dirs=[os.path.join(this_dir, 'csrc')],
extra_compile_args={'cxx': ['-O3',] + generator_flag,
'nvcc':['-O3', '--use_fast_math',
'-gencode', 'arch=compute_70,code=sm_70',
'-gencode', 'arch=compute_80,code=sm_80',
'-gencode', 'arch=compute_90,code=sm_90',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_BFLOAT16_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
'--expt-relaxed-constexpr',
'--expt-extended-lambda'] + generator_flag}))
ext_modules.append(
CUDAExtension(name='unicore_fused_layernorm_backward_gamma_beta',
sources=['csrc/layernorm/interface_gamma_beta.cpp',
'csrc/layernorm/layernorm_backward.cu'],
include_dirs=[os.path.join(this_dir, 'csrc')],
extra_compile_args={'cxx': ['-O3',] + generator_flag,
'nvcc':['-O3', '--use_fast_math', '-maxrregcount=50',
'-gencode', 'arch=compute_70,code=sm_70',
'-gencode', 'arch=compute_80,code=sm_80',
'-gencode', 'arch=compute_90,code=sm_90',
'-U__CUDA_NO_HALF_OPERATORS__',
'-U__CUDA_NO_BFLOAT16_OPERATORS__',
'-U__CUDA_NO_HALF_CONVERSIONS__',
'-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
'--expt-relaxed-constexpr',
'--expt-extended-lambda'] + generator_flag}))
setup(
name="unicore",
version=version,
description="DP Technology's Core AI Framework",
url="https://github.com/dptech-corp/unicore",
classifiers=[
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
setup_requires=[
"setuptools>=18.0",
],
install_requires=[
'numpy; python_version>="3.7"',
"lmdb",
"tqdm",
"torch>=2.0.0",
"ml_collections",
"scipy",
"tensorboardX",
"tokenizers",
"wandb",
],
packages=find_packages(
exclude=[
'build',
'csrc',
"examples",
"examples.*",
"scripts",
"scripts.*",
"tests",
"tests.*",
]
),
ext_modules=ext_modules,
cmdclass=cmdclass,
extras_require=extras,
entry_points={
"console_scripts": [
"unicore-train = unicore_cli.train:cli_main",
],
},
zip_safe=False,
)