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setup.py
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setup.py
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# Copyright 2017 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
# http://www.apache.org/licenses/LICENSE-2.0
# or in the "license" file accompanying this file. This file 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.
# To build and upload a new version, follow the steps below.
# Notes:
# - this is a "Universal Wheels" package that is pure Python and supports both Python2 and Python3
# - Twine is a secure PyPi upload package
# - Make sure you have bumped the version! at mms/version.py
# $ pip install twine
# $ pip install wheel
# $ python setup.py bdist_wheel --universal
# *** TEST YOUR PACKAGE WITH TEST PI ******
# twine upload --repository-url https://test.pypi.org/legacy/ dist/*
# If this is successful then push it to actual pypi
# $ twine upload dist/*
"""
Setup.py for the model server package
"""
import errno
import os
import subprocess
import sys
from datetime import date
from shutil import copy2, rmtree
import setuptools.command.build_py
from setuptools import setup, find_packages, Command
import mms
pkgs = find_packages()
def pypi_description():
"""
Imports the long description for the project page
"""
with open('PyPiDescription.rst') as df:
return df.read()
def detect_model_server_version():
sys.path.append(os.path.abspath("mms"))
if "--release" in sys.argv:
sys.argv.remove("--release")
return mms.__version__.strip()
return mms.__version__.strip() + 'b' + str(date.today()).replace('-', '')
class BuildFrontEnd(setuptools.command.build_py.build_py):
"""
Class defined to run custom commands.
"""
description = 'Build Model Server Frontend'
source_server_file = os.path.abspath('frontend/server/build/libs/server-1.0.jar')
dest_file_name = os.path.abspath('mms/frontend/model-server.jar')
# noinspection PyMethodMayBeStatic
def run(self):
"""
Actual method called to run the build command
:return:
"""
front_end_bin_dir = os.path.abspath('.') + '/mms/frontend'
try:
os.mkdir(front_end_bin_dir)
except OSError as exc:
if exc.errno == errno.EEXIST and os.path.isdir(front_end_bin_dir):
pass
else:
raise
if os.path.exists(self.source_server_file):
os.remove(self.source_server_file)
# Remove build/lib directory.
if os.path.exists('build/lib/'):
rmtree('build/lib/')
try:
subprocess.check_call('frontend/gradlew -p frontend clean build', shell=True)
except OSError:
assert 0, "build failed"
copy2(self.source_server_file, self.dest_file_name)
class BuildPy(setuptools.command.build_py.build_py):
"""
Class to invoke the custom command defined above.
"""
def run(self):
sys.stderr.flush()
self.run_command('build_frontend')
setuptools.command.build_py.build_py.run(self)
class BuildPlugins(Command):
description = 'Build Model Server Plugins'
user_options = [('plugins=', 'p', 'Plugins installed')]
source_plugin_dir = \
os.path.abspath('plugins/build/plugins')
def initialize_options(self):
self.plugins = None
def finalize_options(self):
if self.plugins is None:
print("No plugin option provided. Defaulting to 'default'")
self.plugins = "default"
# noinspection PyMethodMayBeStatic
def run(self):
if os.path.isdir(self.source_plugin_dir):
rmtree(self.source_plugin_dir)
try:
if self.plugins == "sagemaker":
subprocess.check_call('plugins/gradlew -p plugins clean bS', shell=True)
else:
raise OSError("No such rule exists")
except OSError:
assert 0, "build failed"
self.run_command('build_py')
if __name__ == '__main__':
version = detect_model_server_version()
requirements = ['Pillow', 'psutil', 'future', 'model-archiver']
setup(
name='mxnet-model-server',
version=version,
description='Model Server for Apache MXNet is a tool for serving neural net models for inference',
author='MXNet SDK team',
author_email='[email protected]',
long_description=pypi_description(),
url='https://github.com/awslabs/mxnet-model-server',
keywords='MXNet Model Server Serving Deep Learning Inference AI',
packages=pkgs,
cmdclass={
'build_frontend': BuildFrontEnd,
'build_plugins': BuildPlugins,
'build_py': BuildPy,
},
install_requires=requirements,
extras_require={
'mxnet-mkl': ['mxnet-mkl'],
'mxnet-cu90mkl': ['mxnet-cu90mkl'],
'mxnet': ['mxnet'],
},
entry_points={
'console_scripts': [
'mxnet-model-server=mms.model_server:start',
'mxnet-model-export=mms.export_model:main'
]
},
include_package_data=True,
license='Apache License Version 2.0'
)