transformers/setup.py

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# Copyright 2020 The HuggingFace Team. 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.
# 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.
"""
Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/master/setup.py
To create the package for pypi.
1. Change the version in __init__.py, setup.py as well as docs/source/conf.py. Remove the master from the links in
the new models of the README:
(https://huggingface.co/transformers/master/model_doc/ -> https://huggingface.co/transformers/model_doc/)
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then run `make fix-copies` to fix the index of the documentation.
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2. Unpin specific versions from setup.py that use a git install.
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2. Commit these changes with the message: "Release: VERSION"
3. Add a tag in git to mark the release: "git tag VERSION -m'Adds tag VERSION for pypi' "
Push the tag to git: git push --tags origin master
4. Build both the sources and the wheel. Do not change anything in setup.py between
creating the wheel and the source distribution (obviously).
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For the wheel, run: "python setup.py bdist_wheel" in the top level directory.
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(this will build a wheel for the python version you use to build it).
For the sources, run: "python setup.py sdist"
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You should now have a /dist directory with both .whl and .tar.gz source versions.
5. Check that everything looks correct by uploading the package to the pypi test server:
twine upload dist/* -r pypitest
(pypi suggest using twine as other methods upload files via plaintext.)
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You may have to specify the repository url, use the following command then:
twine upload dist/* -r pypitest --repository-url=https://test.pypi.org/legacy/
Check that you can install it in a virtualenv by running:
pip install -i https://testpypi.python.org/pypi transformers
6. Upload the final version to actual pypi:
twine upload dist/* -r pypi
7. Copy the release notes from RELEASE.md to the tag in github once everything is looking hunky-dory.
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8. Add the release version to docs/source/_static/js/custom.js and .circleci/deploy.sh
9. Update README.md to redirect to correct documentation.
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10. Update the version in __init__.py, setup.py to the new version "-dev" and push to master.
"""
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import os
import re
import shutil
from distutils.core import Command
from pathlib import Path
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from setuptools import find_packages, setup
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# Remove stale transformers.egg-info directory to avoid https://github.com/pypa/pip/issues/5466
stale_egg_info = Path(__file__).parent / "transformers.egg-info"
if stale_egg_info.exists():
print(
(
"Warning: {} exists.\n\n"
"If you recently updated transformers to 3.0 or later, this is expected,\n"
"but it may prevent transformers from installing in editable mode.\n\n"
"This directory is automatically generated by Python's packaging tools.\n"
"I will remove it now.\n\n"
"See https://github.com/pypa/pip/issues/5466 for details.\n"
).format(stale_egg_info)
)
shutil.rmtree(stale_egg_info)
# IMPORTANT:
# 1. all dependencies should be listed here with their version requirements if any
# 2. once modified, run: `make deps_table_update` to update src/transformers/dependency_versions_table.py
_deps = [
"black>=20.8b1",
"cookiecutter==1.7.2",
"dataclasses",
"datasets",
"faiss-cpu",
"fastapi",
"filelock",
"flake8>=3.8.3",
"flax==0.2.2",
"fugashi>=1.0",
"ipadic>=1.0.0,<2.0",
"isort>=5.5.4",
"jax>=0.2.0",
"jaxlib==0.1.55",
"keras2onnx",
"numpy",
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"onnxconverter-common",
"onnxruntime-tools>=1.4.2",
"onnxruntime>=1.4.0",
"packaging",
"parameterized",
"protobuf",
"psutil",
"pydantic",
"pytest",
"pytest-xdist",
"python>=3.6.0",
"recommonmark",
"regex!=2019.12.17",
"requests",
"sacremoses",
"scikit-learn",
"sentencepiece==0.1.91",
"sphinx-copybutton",
"sphinx-markdown-tables",
"sphinx-rtd-theme==0.4.3", # sphinx-rtd-theme==0.5.0 introduced big changes in the style.
"sphinx==3.2.1",
"starlette",
"tensorflow-cpu>=2.0",
"tensorflow>=2.0",
"timeout-decorator",
"tokenizers==0.9.4",
"torch>=1.0",
"tqdm>=4.27",
"unidic>=1.0.2",
"unidic_lite>=1.0.7",
"uvicorn",
Conversion script to export transformers models to ONNX IR. (#4253) * Added generic ONNX conversion script for PyTorch model. * WIP initial TF support. * TensorFlow/Keras ONNX export working. * Print framework version info * Add possibility to check the model is correctly loading on ONNX runtime. * Remove quantization option. * Specify ONNX opset version when exporting. * Formatting. * Remove unused imports. * Make functions more generally reusable from other part of the code. * isort happy. * flake happy * Export only feature-extraction for now * Correctly check inputs order / filter before export. * Removed task variable * Fix invalid args call in load_graph_from_args. * Fix invalid args call in convert. * Fix invalid args call in infer_shapes. * Raise exception and catch in caller function instead of exit. * Add 04-onnx-export.ipynb notebook * More WIP on the notebook * Remove unused imports * Simplify & remove unused constants. * Export with constant_folding in PyTorch * Let's try to put function args in the right order this time ... * Disable external_data_format temporary * ONNX notebook draft ready. * Updated notebooks charts + wording * Correct error while exporting last chart in notebook. * Adressing @LysandreJik comment. * Set ONNX opset to 11 as default value. * Set opset param mandatory * Added ONNX export unittests * Quality. * flake8 happy * Add keras2onnx dependency on extras["tf"] * Pin keras2onnx on github master to v1.6.5 * Second attempt. * Third attempt. * Use the right repo URL this time ... * Do the same for onnxconverter-common * Added keras2onnx and onnxconveter-common to 1.7.0 to supports TF2.2 * Correct commit hash. * Addressing PR review: Optimization are enabled by default. * Addressing PR review: small changes in the notebook * setup.py comment about keras2onnx versioning.
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]
# tokenizers: "tokenizers==0.9.4" lookup table
# support non-versions file too so that they can be checked at run time
deps = {b: a for a, b in (re.findall(r"^(([^!=<>]+)(?:[!=<>].*)?$)", x)[0] for x in _deps)}
def deps_list(*pkgs):
return [deps[pkg] for pkg in pkgs]
class DepsTableUpdateCommand(Command):
"""
A custom distutils command that updates the dependency table.
usage: python setup.py deps_table_update
"""
description = "build runtime dependency table"
user_options = [
# format: (long option, short option, description).
("dep-table-update", None, "updates src/transformers/dependency_versions_table.py"),
]
def initialize_options(self):
pass
def finalize_options(self):
pass
def run(self):
entries = "\n".join([f' "{k}": "{v}",' for k, v in deps.items()])
content = [
"# THIS FILE HAS BEEN AUTOGENERATED. To update:",
"# 1. modify the `_deps` dict in setup.py",
"# 2. run `make deps_table_update``",
"deps = {",
entries,
"}",
""
]
target = "src/transformers/dependency_versions_table.py"
print(f"updating {target}")
with open(target, "w", encoding="utf-8", newline="\n") as f:
f.write("\n".join(content))
extras = {}
extras["ja"] = deps_list("fugashi", "ipadic", "unidic_lite", "unidic")
extras["sklearn"] = deps_list("scikit-learn")
extras["tf"] = deps_list("tensorflow", "onnxconverter-common", "keras2onnx")
extras["tf-cpu"] = deps_list("tensorflow-cpu", "onnxconverter-common", "keras2onnx")
extras["torch"] = deps_list("torch")
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if os.name == "nt": # windows
extras["retrieval"] = deps_list("datasets") # faiss is not supported on windows
extras["flax"] = [] # jax is not supported on windows
else:
extras["retrieval"] = deps_list("faiss-cpu", "datasets")
extras["flax"] = deps_list("jax", "jaxlib", "flax")
extras["tokenizers"] = deps_list("tokenizers")
extras["onnxruntime"] = deps_list("onnxruntime", "onnxruntime-tools")
extras["modelcreation"] = deps_list("cookiecutter")
extras["serving"] = deps_list("pydantic", "uvicorn", "fastapi", "starlette")
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extras["sentencepiece"] = deps_list("sentencepiece", "protobuf")
extras["retrieval"] = deps_list("faiss-cpu", "datasets")
extras["testing"] = (
deps_list("pytest", "pytest-xdist", "timeout-decorator", "parameterized", "psutil")
+ extras["retrieval"]
+ extras["modelcreation"]
)
extras["docs"] = deps_list("recommonmark", "sphinx", "sphinx-markdown-tables", "sphinx-rtd-theme", "sphinx-copybutton")
extras["quality"] = deps_list("black", "isort", "flake8")
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extras["all"] = extras["tf"] + extras["torch"] + extras["flax"] + extras["sentencepiece"] + extras["tokenizers"]
extras["dev"] = (
extras["all"]
+ extras["testing"]
+ extras["quality"]
+ extras["ja"]
+ extras["docs"]
+ extras["sklearn"]
+ extras["modelcreation"]
)
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# when modifying the following list, make sure to update src/transformers/dependency_versions_check.py
install_requires = [
deps["dataclasses"] + ";python_version<'3.7'", # dataclasses for Python versions that don't have it
deps["filelock"], # filesystem locks, e.g., to prevent parallel downloads
deps["numpy"],
deps["packaging"], # utilities from PyPA to e.g., compare versions
deps["regex"], # for OpenAI GPT
deps["requests"], # for downloading models over HTTPS
deps["sacremoses"], # for XLM
deps["tokenizers"],
deps["tqdm"], # progress bars in model download and training scripts
]
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setup(
name="transformers",
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version="4.1.0.dev0",
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author="Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Sam Shleifer, Patrick von Platen, Sylvain Gugger, Google AI Language Team Authors, Open AI team Authors, Facebook AI Authors, Carnegie Mellon University Authors",
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author_email="thomas@huggingface.co",
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description="State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch",
long_description=open("README.md", "r", encoding="utf-8").read(),
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long_description_content_type="text/markdown",
keywords="NLP deep learning transformer pytorch tensorflow BERT GPT GPT-2 google openai CMU",
license="Apache",
url="https://github.com/huggingface/transformers",
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package_dir={"": "src"},
packages=find_packages("src"),
extras_require=extras,
entry_points={"console_scripts": ["transformers-cli=transformers.commands.transformers_cli:main"]},
python_requires=">=3.6.0",
install_requires=install_requires,
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classifiers=[
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"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
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"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.6",
"Programming Language :: Python :: 3.7",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
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],
cmdclass={"deps_table_update": DepsTableUpdateCommand},
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)