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# 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,
},
)
)
ext_modules.append(
CUDAExtension(
name="unicore_fused_rmsnorm",
sources=["csrc/rmsnorm/interface.cpp", "csrc/rmsnorm/rmsnorm.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_rmsnorm_backward_gamma",
sources=[
"csrc/rmsnorm/interface_gamma.cpp",
"csrc/rmsnorm/rmsnorm_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,
)
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