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setup.py
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#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You 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.
#
"""Setup.py module for the workflow's worker utilities.
All the workflow related code is gathered in a package that will be built as a
source distribution, staged in the staging area for the workflow being run and
then installed in the workers when they start running.
This behavior is triggered by specifying the --setup_file command line option
when running the workflow for remote execution.
"""
# pytype: skip-file
from __future__ import absolute_import
from __future__ import print_function
import subprocess
from distutils.command.build import build as _build # type: ignore
import setuptools
# This class handles the pip install mechanism.
class build(_build): # pylint: disable=invalid-name
"""A build command class that will be invoked during package install.
The package built using the current setup.py will be staged and later
installed in the worker using `pip install package'. This class will be
instantiated during install for this specific scenario and will trigger
running the custom commands specified.
"""
sub_commands = _build.sub_commands + [('CustomCommands', None)]
# Some custom command to run during setup. The command is not essential for this
# workflow. It is used here as an example. Each command will spawn a child
# process. Typically, these commands will include steps to install non-Python
# packages. For instance, to install a C++-based library libjpeg62 the following
# two commands will have to be added:
#
# ['apt-get', 'update'],
# ['apt-get', '--assume-yes', 'install', 'libjpeg62'],
#
# First, note that there is no need to use the sudo command because the setup
# script runs with appropriate access.
# Second, if apt-get tool is used then the first command needs to be 'apt-get
# update' so the tool refreshes itself and initializes links to download
# repositories. Without this initial step the other apt-get install commands
# will fail with package not found errors. Note also --assume-yes option which
# shortcuts the interactive confirmation.
#
# Note that in this example custom commands will run after installing required
# packages. If you have a PyPI package that depends on one of the custom
# commands, move installation of the dependent package to the list of custom
# commands, e.g.:
#
# ['pip', 'install', 'my_package'],
#
# TODO(BEAM-3237): Output from the custom commands are missing from the logs.
# The output of custom commands (including failures) will be logged in the
# worker-startup log.
CUSTOM_COMMANDS = [
['echo', 'Custom command worked!'],
#['pip3', 'install','https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.2.5/en_core_web_sm-2.2.5.tar.gz'],
#['wget', '-P','/home/','https://storage.cloud.google.com/ds-playground/squash/bert.tar.gz?organizationId=399341007699'],
#['wget', '-P','/home/','https://storage.cloud.google.com/ds-playground/squash/gpt2_qa.tar.gz'],
#['tar','-zxvf', '/home/bert.tar.gz'],
#['tar','-zxvf', '/home/gpt2_qa.tar.gz'],
]
class CustomCommands(setuptools.Command):
"""A setuptools Command class able to run arbitrary commands."""
def initialize_options(self):
pass
def finalize_options(self):
pass
def RunCustomCommand(self, command_list):
print('Running command: %s' % command_list)
p = subprocess.Popen(
command_list,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
# Can use communicate(input='y\n'.encode()) if the command run requires
# some confirmation.
stdout_data, _ = p.communicate()
print('Command output: %s' % stdout_data)
if p.returncode != 0:
raise RuntimeError(
'Command %s failed: exit code: %s' % (command_list, p.returncode))
def run(self):
for command in CUSTOM_COMMANDS:
self.RunCustomCommand(command)
# Configure the required packages and scripts to install.
# Note that the Python Dataflow containers come with numpy already installed
# so this dependency will not trigger anything to be installed unless a version
# restriction is specified.
"""
REQUIRED_PACKAGES = [
#"git+git://github.com/robinsingh1/pytorch-pretrained-BERT@master#pytorch-pretrained-BERT",
"pytorch-pretrained-BERT",
"pytorch-ignite",
"torch",
#"transformers==2.5.1",
#"tensorboardX==1.8",
#"tensorflow",
"spacy==2.2.4",
#"https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.1.0/en_core_web_sm-2.1.0.tar.gz",
#"https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.2.0/en_core_web_sm-2.2.0.tar.gz#egg=en_core_web_sm",
"tqdm",
"torchvision",
"dotmap"
]
"""
#REQUIRED_PACKAGES = []
REQUIRED_PACKAGES = []
setuptools.setup(
name='juliaset',
version='0.0.1',
description='Julia set workflow package.',
install_requires=REQUIRED_PACKAGES,
packages=setuptools.find_packages(),
include_package_data=True,
#packages=setuptools.find_packages()
#data_files=[(".", ["query.sql"])],
#package_data={'question_generation': ['gpt2_corefs_question_generation/*'],
# 'question_answering': ['bert_large_qa_model/*']},
cmdclass={
# Command class instantiated and run during pip install scenarios.
'build': build,
'CustomCommands': CustomCommands,
}
package_data={'question_generation':
['gpt2_corefs_question_generation/*']
}
)