spaCy/setup.py

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#!/usr/bin/env python
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from __future__ import print_function
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import io
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import os
import subprocess
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import sys
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import contextlib
from distutils.command.build_ext import build_ext
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from distutils.sysconfig import get_python_inc
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import distutils.util
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from distutils import ccompiler, msvccompiler
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from setuptools import Extension, setup, find_packages
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def is_new_osx():
"""Check whether we're on OSX >= 10.10"""
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name = distutils.util.get_platform()
if sys.platform != "darwin":
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return False
elif name.startswith("macosx-10"):
minor_version = int(name.split("-")[1].split(".")[1])
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if minor_version >= 7:
return True
else:
return False
else:
return False
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PACKAGE_DATA = {"": ["*.pyx", "*.pxd", "*.txt", "*.tokens", "*.json"]}
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PACKAGES = find_packages()
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MOD_NAMES = [
"spacy._align",
"spacy.parts_of_speech",
"spacy.strings",
"spacy.lexeme",
"spacy.vocab",
"spacy.attrs",
"spacy.morphology",
"spacy.pipeline.pipes",
"spacy.syntax.stateclass",
"spacy.syntax._state",
"spacy.tokenizer",
"spacy.syntax.nn_parser",
"spacy.syntax._parser_model",
"spacy.syntax._beam_utils",
"spacy.syntax.nonproj",
"spacy.syntax.transition_system",
"spacy.syntax.arc_eager",
"spacy.gold",
"spacy.tokens.doc",
"spacy.tokens.span",
"spacy.tokens.token",
"spacy.tokens._retokenize",
"spacy.matcher.matcher",
"spacy.matcher.phrasematcher",
"spacy.matcher.dependencymatcher",
"spacy.syntax.ner",
"spacy.symbols",
"spacy.vectors",
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]
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COMPILE_OPTIONS = {
"msvc": ["/Ox", "/EHsc"],
"mingw32": ["-O2", "-Wno-strict-prototypes", "-Wno-unused-function"],
"other": ["-O2", "-Wno-strict-prototypes", "-Wno-unused-function"],
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}
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LINK_OPTIONS = {"msvc": [], "mingw32": [], "other": []}
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if is_new_osx():
# On Mac, use libc++ because Apple deprecated use of
# libstdc
COMPILE_OPTIONS["other"].append("-stdlib=libc++")
LINK_OPTIONS["other"].append("-lc++")
# g++ (used by unix compiler on mac) links to libstdc++ as a default lib.
# See: https://stackoverflow.com/questions/1653047/avoid-linking-to-libstdc
LINK_OPTIONS["other"].append("-nodefaultlibs")
USE_OPENMP_DEFAULT = "0" if sys.platform != "darwin" else None
if os.environ.get("USE_OPENMP", USE_OPENMP_DEFAULT) == "1":
if sys.platform == "darwin":
COMPILE_OPTIONS["other"].append("-fopenmp")
LINK_OPTIONS["other"].append("-fopenmp")
PACKAGE_DATA["spacy.platform.darwin.lib"] = ["*.dylib"]
PACKAGES.append("spacy.platform.darwin.lib")
elif sys.platform == "win32":
COMPILE_OPTIONS["msvc"].append("/openmp")
else:
COMPILE_OPTIONS["other"].append("-fopenmp")
LINK_OPTIONS["other"].append("-fopenmp")
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# By subclassing build_extensions we have the actual compiler that will be used which is really known only after finalize_options
# http://stackoverflow.com/questions/724664/python-distutils-how-to-get-a-compiler-that-is-going-to-be-used
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class build_ext_options:
def build_options(self):
for e in self.extensions:
e.extra_compile_args += COMPILE_OPTIONS.get(
self.compiler.compiler_type, COMPILE_OPTIONS["other"]
)
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for e in self.extensions:
e.extra_link_args += LINK_OPTIONS.get(
self.compiler.compiler_type, LINK_OPTIONS["other"]
)
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class build_ext_subclass(build_ext, build_ext_options):
def build_extensions(self):
build_ext_options.build_options(self)
build_ext.build_extensions(self)
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def generate_cython(root, source):
print("Cythonizing sources")
p = subprocess.call(
[sys.executable, os.path.join(root, "bin", "cythonize.py"), source],
env=os.environ,
)
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if p != 0:
raise RuntimeError("Running cythonize failed")
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def is_source_release(path):
return os.path.exists(os.path.join(path, "PKG-INFO"))
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def clean(path):
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for name in MOD_NAMES:
name = name.replace(".", "/")
for ext in [".so", ".html", ".cpp", ".c"]:
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file_path = os.path.join(path, name + ext)
if os.path.exists(file_path):
os.unlink(file_path)
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@contextlib.contextmanager
def chdir(new_dir):
old_dir = os.getcwd()
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try:
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os.chdir(new_dir)
sys.path.insert(0, new_dir)
yield
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finally:
del sys.path[0]
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os.chdir(old_dir)
def setup_package():
root = os.path.abspath(os.path.dirname(__file__))
if len(sys.argv) > 1 and sys.argv[1] == "clean":
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return clean(root)
with chdir(root):
with io.open(os.path.join(root, "spacy", "about.py"), encoding="utf8") as f:
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about = {}
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exec(f.read(), about)
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with io.open(os.path.join(root, "README.md"), encoding="utf8") as f:
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readme = f.read()
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include_dirs = [
get_python_inc(plat_specific=True),
os.path.join(root, "include"),
]
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if (
ccompiler.new_compiler().compiler_type == "msvc"
and msvccompiler.get_build_version() == 9
):
include_dirs.append(os.path.join(root, "include", "msvc9"))
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ext_modules = []
for mod_name in MOD_NAMES:
mod_path = mod_name.replace(".", "/") + ".cpp"
extra_link_args = []
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extra_compile_args = []
# ???
# Imported from patch from @mikepb
# See Issue #267. Running blind here...
if sys.platform == "darwin":
dylib_path = [".." for _ in range(mod_name.count("."))]
dylib_path = "/".join(dylib_path)
dylib_path = "@loader_path/%s/spacy/platform/darwin/lib" % dylib_path
extra_link_args.append("-Wl,-rpath,%s" % dylib_path)
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ext_modules.append(
Extension(
mod_name,
[mod_path],
language="c++",
include_dirs=include_dirs,
extra_link_args=extra_link_args,
)
)
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if not is_source_release(root):
generate_cython(root, "spacy")
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setup(
name=about["__title__"],
zip_safe=False,
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packages=PACKAGES,
package_data=PACKAGE_DATA,
description=about["__summary__"],
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long_description=readme,
long_description_content_type="text/markdown",
author=about["__author__"],
author_email=about["__email__"],
version=about["__version__"],
url=about["__uri__"],
license=about["__license__"],
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ext_modules=ext_modules,
scripts=["bin/spacy"],
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install_requires=[
"numpy>=1.15.0",
💫 Use Blis for matrix multiplications (#2966) Our epic matrix multiplication odyssey is drawing to a close... I've now finally got the Blis linear algebra routines in a self-contained Python package, with wheels for Windows, Linux and OSX. The only missing platform at the moment is Windows Python 2.7. The result is at https://github.com/explosion/cython-blis Thinc v7.0.0 will make the change to Blis. I've put a Thinc v7.0.0.dev0 up on PyPi so that we can test these changes with the CI, and even get them out to spacy-nightly, before Thinc v7.0.0 is released. This PR also updates the other dependencies to be in line with the current versions master is using. I've also resolved the msgpack deprecation problems, and gotten spaCy and Thinc up to date with the latest Cython. The point of switching to Blis is to have control of how our matrix multiplications are executed across platforms. When we were using numpy for this, a different library would be used on pip and conda, OSX would use Accelerate, etc. This would open up different bugs and performance problems, especially when multi-threading was introduced. With the change to Blis, we now strictly single-thread the matrix multiplications. This will make it much easier to use multiprocessing to parallelise the runtime, since we won't have nested parallelism problems to deal with. * Use blis * Use -2 arg to Cython * Update dependencies * Fix requirements * Update setup dependencies * Fix requirement typo * Fix msgpack errors * Remove Python27 test from Appveyor, until Blis works there * Auto-format setup.py * Fix murmurhash version
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"murmurhash>=0.28.0,<1.1.0",
"cymem>=2.0.2,<2.1.0",
"preshed>=2.0.1,<2.1.0",
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"thinc==7.0.1.dev0",
💫 Use Blis for matrix multiplications (#2966) Our epic matrix multiplication odyssey is drawing to a close... I've now finally got the Blis linear algebra routines in a self-contained Python package, with wheels for Windows, Linux and OSX. The only missing platform at the moment is Windows Python 2.7. The result is at https://github.com/explosion/cython-blis Thinc v7.0.0 will make the change to Blis. I've put a Thinc v7.0.0.dev0 up on PyPi so that we can test these changes with the CI, and even get them out to spacy-nightly, before Thinc v7.0.0 is released. This PR also updates the other dependencies to be in line with the current versions master is using. I've also resolved the msgpack deprecation problems, and gotten spaCy and Thinc up to date with the latest Cython. The point of switching to Blis is to have control of how our matrix multiplications are executed across platforms. When we were using numpy for this, a different library would be used on pip and conda, OSX would use Accelerate, etc. This would open up different bugs and performance problems, especially when multi-threading was introduced. With the change to Blis, we now strictly single-thread the matrix multiplications. This will make it much easier to use multiprocessing to parallelise the runtime, since we won't have nested parallelism problems to deal with. * Use blis * Use -2 arg to Cython * Update dependencies * Fix requirements * Update setup dependencies * Fix requirement typo * Fix msgpack errors * Remove Python27 test from Appveyor, until Blis works there * Auto-format setup.py * Fix murmurhash version
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"blis>=0.2.2,<0.3.0",
"plac<1.0.0,>=0.9.6",
"requests>=2.13.0,<3.0.0",
💫 New JSON helpers, training data internals & CLI rewrite (#2932) * Support nowrap setting in util.prints * Tidy up and fix whitespace * Simplify script and use read_jsonl helper * Add JSON schemas (see #2928) * Deprecate Doc.print_tree Will be replaced with Doc.to_json, which will produce a unified format * Add Doc.to_json() method (see #2928) Converts Doc objects to JSON using the same unified format as the training data. Method also supports serializing selected custom attributes in the doc._. space. * Remove outdated test * Add write_json and write_jsonl helpers * WIP: Update spacy train * Tidy up spacy train * WIP: Use wasabi for formatting * Add GoldParse helpers for JSON format * WIP: add debug-data command * Fix typo * Add missing import * Update wasabi pin * Add missing import * 💫 Refactor CLI (#2943) To be merged into #2932. ## Description - [x] refactor CLI To use [`wasabi`](https://github.com/ines/wasabi) - [x] use [`black`](https://github.com/ambv/black) for auto-formatting - [x] add `flake8` config - [x] move all messy UD-related scripts to `cli.ud` - [x] make converters function that take the opened file and return the converted data (instead of having them handle the IO) ### Types of change enhancement ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information. * Update wasabi pin * Delete old test * Update errors * Fix typo * Tidy up and format remaining code * Fix formatting * Improve formatting of messages * Auto-format remaining code * Add tok2vec stuff to spacy.train * Fix typo * Update wasabi pin * Fix path checks for when train() is called as function * Reformat and tidy up pretrain script * Update argument annotations * Raise error if model language doesn't match lang * Document new train command
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"jsonschema>=2.6.0,<3.0.0",
"wasabi>=0.0.12,<1.1.0",
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"srsly>=0.0.5,<1.1.0",
'pathlib==1.0.1; python_version < "3.4"',
],
setup_requires=["wheel"],
extras_require={
"cuda": ["cupy>=4.0"],
"cuda80": ["cupy-cuda80>=4.0"],
"cuda90": ["cupy-cuda90>=4.0"],
"cuda91": ["cupy-cuda91>=4.0"],
💫 Use Blis for matrix multiplications (#2966) Our epic matrix multiplication odyssey is drawing to a close... I've now finally got the Blis linear algebra routines in a self-contained Python package, with wheels for Windows, Linux and OSX. The only missing platform at the moment is Windows Python 2.7. The result is at https://github.com/explosion/cython-blis Thinc v7.0.0 will make the change to Blis. I've put a Thinc v7.0.0.dev0 up on PyPi so that we can test these changes with the CI, and even get them out to spacy-nightly, before Thinc v7.0.0 is released. This PR also updates the other dependencies to be in line with the current versions master is using. I've also resolved the msgpack deprecation problems, and gotten spaCy and Thinc up to date with the latest Cython. The point of switching to Blis is to have control of how our matrix multiplications are executed across platforms. When we were using numpy for this, a different library would be used on pip and conda, OSX would use Accelerate, etc. This would open up different bugs and performance problems, especially when multi-threading was introduced. With the change to Blis, we now strictly single-thread the matrix multiplications. This will make it much easier to use multiprocessing to parallelise the runtime, since we won't have nested parallelism problems to deal with. * Use blis * Use -2 arg to Cython * Update dependencies * Fix requirements * Update setup dependencies * Fix requirement typo * Fix msgpack errors * Remove Python27 test from Appveyor, until Blis works there * Auto-format setup.py * Fix murmurhash version
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"cuda92": ["cupy-cuda92>=4.0"],
"cuda100": ["cupy-cuda100>=4.0"],
},
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python_requires=">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*",
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classifiers=[
"Development Status :: 5 - Production/Stable",
"Environment :: Console",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Operating System :: POSIX :: Linux",
"Operating System :: MacOS :: MacOS X",
"Operating System :: Microsoft :: Windows",
"Programming Language :: Cython",
"Programming Language :: Python :: 2",
"Programming Language :: Python :: 2.7",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.4",
"Programming Language :: Python :: 3.5",
"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Topic :: Scientific/Engineering",
],
cmdclass={"build_ext": build_ext_subclass},
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)
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if __name__ == "__main__":
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setup_package()