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setup.py
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setup.py
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import glob
import os
import shutil
import subprocess
import sys
from setuptools import setup, find_packages
IS_WINDOWS = sys.platform == "win32"
def get_cuda_version(cuda_home):
"""Locate the CUDA version."""
version_file = os.path.join(cuda_home, "version.txt")
try:
if os.path.isfile(version_file):
with open(version_file, "r") as f_version:
version_str = f_version.readline().replace("\n", "").replace(
"\r", "")
return version_str.split(" ")[2][:4]
else:
version_str = subprocess.check_output(
[os.path.join(cuda_home, "bin", "nvcc"), "--version"])
version_str = str(version_str).replace("\n", "").replace("\r", "")
idx = version_str.find("release")
return version_str[idx + len("release "):idx + len("release ") + 4]
except RuntimeError:
raise RuntimeError("Cannot read cuda version file")
def locate_cuda():
"""Locate the CUDA environment on the system."""
# Guess #1
cuda_home = os.environ.get("CUDA_HOME") or os.environ.get("CUDA_PATH")
if cuda_home is None:
# Guess #2
try:
which = "where" if IS_WINDOWS else "which"
nvcc = subprocess.check_output([which,
"nvcc"]).decode().rstrip("\r\n")
cuda_home = os.path.dirname(os.path.dirname(nvcc))
except subprocess.CalledProcessError:
# Guess #3
if IS_WINDOWS:
cuda_homes = glob.glob(
"C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v*.*")
if len(cuda_homes) == 0:
cuda_home = ""
else:
cuda_home = cuda_homes[0]
else:
cuda_home = "/usr/local/cuda"
if not os.path.exists(cuda_home):
cuda_home = None
version = get_cuda_version(cuda_home)
cudaconfig = {
"home":
cuda_home,
"include":
os.path.join(cuda_home, "include"),
"lib64":
os.path.join(cuda_home,
os.path.join("lib", "x64") if IS_WINDOWS else "lib64"),
}
if not all([os.path.exists(v) for v in cudaconfig.values()]):
raise EnvironmentError(
"The CUDA path could not be located in $PATH, $CUDA_HOME or $CUDA_PATH. "
"Either add it to your path, or set $CUDA_HOME or $CUDA_PATH.")
return cudaconfig, version
def get_cuda_version_str(no_dot=False):
"""Return the cuda version in the format of [x.x]."""
ver = locate_cuda()[1]
if no_dot:
ver = ver.replace(".", "")
return ver
install_require_list = [
"tqdm",
"ray[default]",
"jax==0.3.5",
"flax==0.4.1",
"pulp",
"tensorstore",
"numpy==1.20",
"numba",
]
dev_require_list = [
f"cupy-cuda{get_cuda_version_str(no_dot=True)}", "yapf==0.32.0",
"pylint==2.14.0", "cmake", "pybind11"
]
doc_require_list = [
"sphinx", "sphinx-rtd-theme", "sphinx-gallery", "matplotlib"
]
def build():
"""Build the custom pipeline marker API."""
# Check cuda version
build_command = []
if "CUDACXX" in os.environ and os.path.exists(os.environ["CUDACXX"]):
cudacxx_path = os.environ["CUDACXX"]
else:
# infer CUDACXX
cuda_version = get_cuda_version_str()
cudacxx_path = f"/usr/local/cuda-{cuda_version}/bin/nvcc"
if not os.path.exists(cudacxx_path):
raise ValueError("Cannot find CUDACXX compiler.")
# Enter the folder and build
build_command += [f"cd alpa/pipeline_parallel/xla_custom_call_marker; "]
build_command += [f"CUDACXX={cudacxx_path} ./build.sh"]
build_command = " ".join(build_command)
print(build_command)
ret = subprocess.call(build_command, shell=True)
if ret != 0:
raise RuntimeError("Failed to build the pipeline markers "
f"with exit code {ret}")
def move_file(target_dir, filename):
source = filename
destination = os.path.join(
target_dir, "alpa/pipeline_parallel/xla_custom_call_marker/build",
filename.split('/')[-1])
# Create the target directory if it doesn't already exist.
os.makedirs(os.path.dirname(destination), exist_ok=True)
if not os.path.exists(destination):
print("Copying {} to {}.".format(source, destination))
if IS_WINDOWS:
# Does not preserve file mode (needed to avoid read-only bit)
shutil.copyfile(source, destination, follow_symlinks=True)
else:
# Preserves file mode (needed to copy executable bit)
shutil.copy(source, destination, follow_symlinks=True)
def build_and_move(build_ext):
build()
files_to_include = glob.glob(
"alpa/pipeline_parallel/xla_custom_call_marker/build/*.so")
for filename in files_to_include:
move_file(build_ext.build_lib, filename)
if __name__ == "__main__":
import setuptools
import setuptools.command.build_ext
from setuptools.command.install import install
class build_ext(setuptools.command.build_ext.build_ext):
def run(self):
return build_and_move(self)
class BinaryDistribution(setuptools.Distribution):
def has_ext_modules(self):
return True
class InstallPlatlib(install):
def finalize_options(self):
install.finalize_options(self)
if self.distribution.has_ext_modules():
self.install_lib = self.install_platlib
with open(os.path.join("README.md"), encoding="utf-8") as f:
long_description = f.read()
setup(
name="alpa",
version=os.environ.get("VERSION"),
author="Alpa team",
author_email="",
description=
"Alpa automatically parallelizes large tensor computation graphs and "
"runs them on a distributed cluster.",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/alpa-projects/alpa",
classifiers=[
'Programming Language :: Python :: 3',
'Topic :: Scientific/Engineering :: Artificial Intelligence'
],
keywords=("alpa distributed parallel machine-learning model-parallelism"
"gpt-3 deep-learning language-model python"),
packages=find_packages(exclude=["playground"]),
python_requires='>=3.7',
cmdclass={
"build_ext": build_ext,
"install": InstallPlatlib
},
distclass=BinaryDistribution,
install_requires=install_require_list,
extras_require={
'dev': dev_require_list,
'doc': doc_require_list + dev_require_list,
},
)