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setup.py
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setup.py
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#!/usr/bin/env python
#
# Copyright 2016 The BigDL Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import fnmatch
from setuptools import setup
import urllib.request
import os
import stat
long_description = '''
BigDL Nano automatically accelerates TensorFlow and PyTorch pipelines
by applying modern CPU optimizations.
See [here](https://bigdl.readthedocs.io/en/latest/doc/Nano/Overview/nano.html)
for more information.
'''
exclude_patterns = ["*__pycache__*", "lightning_logs", "recipe", "setup.py"]
nano_home = os.path.join(os.path.dirname(os.path.abspath(__file__)), "src")
BIGDL_PYTHON_HOME = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
VERSION = open(os.path.join(BIGDL_PYTHON_HOME, 'version.txt'), 'r').read().strip()
lib_urls = [
"https://github.com/analytics-zoo/jemalloc/releases/download/v5.3.0/libjemalloc.so",
"https://github.com/analytics-zoo/jemalloc/releases/download/v5.3.0/libjemalloc.dylib",
"https://github.com/analytics-zoo/libjpeg-turbo/releases/download/v2.1.4/libturbojpeg.so.0.2.0",
"https://github.com/analytics-zoo/tcmalloc/releases/download/v2.10/libtcmalloc.so"
]
def get_nano_packages():
nano_packages = []
for dirpath, _, _ in os.walk(os.path.join(nano_home, "bigdl")):
print(dirpath)
package = dirpath.split(nano_home + os.sep)[1].replace(os.sep, '.')
if any(fnmatch.fnmatchcase(package, pat=pattern)
for pattern in exclude_patterns):
print("excluding", package)
else:
nano_packages.append(package)
print("including", package)
return nano_packages
def download_libs(url: str):
libs_dir = os.path.join(nano_home, "bigdl", "nano", "libs")
if not os.path.exists(libs_dir):
os.makedirs(libs_dir, exist_ok=True)
libso_file_name = url.split('/')[-1]
libso_file = os.path.join(libs_dir, libso_file_name)
if not os.path.exists(libso_file):
urllib.request.urlretrieve(url, libso_file)
st = os.stat(libso_file)
os.chmod(libso_file, st.st_mode | stat.S_IEXEC)
def setup_package():
# all intel-tensorflow is only avaliable for linux and windows now
tensorflow_27_requires = ["intel-tensorflow==2.7.0; (platform_machine=='x86_64' or platform_machine == 'AMD64') and \
platform_system!='Darwin'",
"tensorflow==2.7.0; platform_machine=='x86_64' and \
platform_system=='Darwin'"]
tensorflow_28_requires = ["intel-tensorflow==2.8.0; (platform_machine=='x86_64' or platform_machine == 'AMD64') and \
platform_system!='Darwin'",
"tensorflow==2.8.0; platform_machine=='x86_64' and \
platform_system=='Darwin'"]
tensorflow_29_requires = ["intel-tensorflow==2.9.1; (platform_machine=='x86_64' or platform_machine == 'AMD64') and \
platform_system!='Darwin'",
"tensorflow==2.9.0; platform_machine=='x86_64' and \
platform_system=='Darwin'"]
tensorflow_210_requires = ["intel-tensorflow==2.10.0; (platform_machine=='x86_64' or platform_machine == 'AMD64') and \
platform_system!='Darwin'",
"tensorflow==2.10.0; platform_machine=='x86_64' and \
platform_system=='Darwin'"]
# options for stock tensorflow
stock_tensorflow_27_requires = ["tensorflow==2.7.4; (platform_machine=='x86_64' or platform_machine == 'AMD64')"]
stock_tensorflow_28_requires = ["tensorflow==2.8.4; (platform_machine=='x86_64' or platform_machine == 'AMD64')"]
stock_tensorflow_29_requires = ["tensorflow==2.9.3; (platform_machine=='x86_64' or platform_machine == 'AMD64')"]
stock_tensorflow_210_requires = ["tensorflow==2.10.1; (platform_machine=='x86_64' or platform_machine == 'AMD64')"]
tensorflow_common_requires = ["tf2onnx==1.13.0; (platform_machine=='x86_64' or platform_machine == 'AMD64')"]
# default tensorflow_dep
tensorflow_requires = tensorflow_29_requires + tensorflow_common_requires
tensorflow_210_requires += tensorflow_common_requires
tensorflow_29_requires += tensorflow_common_requires
tensorflow_28_requires += tensorflow_common_requires
tensorflow_27_requires += tensorflow_common_requires
stock_tensorflow_27_requires += tensorflow_common_requires
stock_tensorflow_28_requires += tensorflow_common_requires
stock_tensorflow_29_requires += tensorflow_common_requires
stock_tensorflow_210_requires += tensorflow_common_requires
# ipex is only avaliable for linux now
pytorch_20_requires = ["torch==2.0.0",
"torchvision==0.15.1",
"intel_extension_for_pytorch==2.0.0;platform_system=='Linux'"]
pytorch_113_requires = ["torch==1.13.1",
"torchvision==0.14.1",
"intel_extension_for_pytorch==1.13.100;platform_system=='Linux'"]
# This is for xpu support (currently we only support 1.13)
# should be installed with -f https://developer.intel.com/ipex-whl-stable-xpu
pytorch_113_xpu_requires = ["torch==1.13.0a0",
"torchvision==0.14.1a0",
"intel_extension_for_pytorch==1.13.10+xpu;platform_system=='Linux'"]
pytorch_112_requires = ["torch==1.12.1",
"torchvision==0.13.1",
"intel_extension_for_pytorch==1.12.300;platform_system=='Linux'"]
pytorch_111_requires = ["torch==1.11.0",
"torchvision==0.12.0",
"intel_extension_for_pytorch==1.11.0;platform_system=='Linux'"]
pytorch_110_requires = ["torch==1.10.1",
"torchvision==0.11.2",
"intel_extension_for_pytorch==1.10.100;platform_system=='Linux'"]
# this require install option --extra-index-url https://download.pytorch.org/whl/nightly/
pytorch_nightly_requires = ["torch~=1.14.0.dev",
"torchvision~=0.15.0.dev"]
pytorch_common_requires = ["pytorch_lightning==1.6.4",
"torchmetrics==0.11.0",
"opencv-python-headless",
"PyTurboJPEG",
"opencv-transforms",
"cryptography==39.0.1"]
# default pytorch_dep
pytorch_requires = pytorch_113_requires + pytorch_common_requires
pytorch_20_requires += pytorch_common_requires
pytorch_113_requires += pytorch_common_requires
pytorch_113_xpu_requires += pytorch_common_requires
pytorch_112_requires += pytorch_common_requires
pytorch_111_requires += pytorch_common_requires
pytorch_110_requires += pytorch_common_requires
pytorch_nightly_requires += pytorch_common_requires
inference_requires = ["onnx==1.12.0",
"onnxruntime==1.12.1",
"onnxruntime-extensions==0.7.0; platform_system!='Darwin'",
"onnxruntime-extensions==0.3.1; (platform_machine=='x86_64' or platform_machine == 'AMD64') and \
platform_system=='Darwin'",
"openvino-dev==2022.3.0",
"neural-compressor==2.0; platform_system!='Windows'",
"onnxsim==0.4.8; platform_system!='Darwin'",
"onnxsim==0.4.1; (platform_machine=='x86_64' or platform_machine == 'AMD64') and \
platform_system=='Darwin'"]
install_requires = ["intel-openmp; (platform_machine=='x86_64' or platform_machine == 'AMD64')",
"cloudpickle",
"protobuf==3.19.5",
"py-cpuinfo",
"pyyaml",
"packaging",
"sigfig",
"setuptools<66"]
package_data = [
"libs/libjemalloc.so",
"libs/libturbojpeg.so.0.2.0",
"libs/libtcmalloc.so"
]
for url in lib_urls:
download_libs(url)
scripts = ["scripts/bigdl-nano-init",
"scripts/bigdl-nano-init.ps1",
"scripts/bigdl-nano-unset-env",
"scripts/bigdl-nano-unset-env.ps1"]
metadata = dict(
name='bigdl-nano',
version=VERSION,
description='High-performance scalable acceleration components for intel.',
long_description=long_description,
long_description_content_type="text/markdown",
author='BigDL Authors',
author_email='bigdl-user-group@googlegroups.com',
url='https://github.com/intel-analytics/BigDL',
install_requires=install_requires,
extras_require={"tensorflow": tensorflow_requires,
"tensorflow_27": tensorflow_27_requires,
"tensorflow_28": tensorflow_28_requires,
"tensorflow_29": tensorflow_29_requires,
"tensorflow_210": tensorflow_210_requires,
"stock_tensorflow_27": stock_tensorflow_27_requires,
"stock_tensorflow_28": stock_tensorflow_28_requires,
"stock_tensorflow_29": stock_tensorflow_29_requires,
"stock_tensorflow_210": stock_tensorflow_210_requires,
"pytorch": pytorch_requires,
"pytorch_20": pytorch_20_requires,
"pytorch_113": pytorch_113_requires,
"pytorch_112": pytorch_112_requires,
"pytorch_111": pytorch_111_requires,
"pytorch_110": pytorch_110_requires,
"pytorch_113_xpu": pytorch_113_xpu_requires,
"pytorch_nightly": pytorch_nightly_requires,
"inference": inference_requires},
package_data={"bigdl.nano": package_data},
scripts=scripts,
package_dir={"": "src"},
entry_points = {
'console_scripts': ['bigdl-submit=bigdl.nano.k8s:main'],
},
packages=get_nano_packages(),
)
setup(**metadata)
if __name__ == '__main__':
setup_package()