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setup.py
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setup.py
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# Lint as: python3
""" HuggingFace/Evaluate is an open library for evaluation.
Note:
VERSION needs to be formatted following the MAJOR.MINOR.PATCH convention
(we need to follow this convention to be able to retrieve versioned scripts)
To create the package for pypi.
1. Open a PR and change the version in:
- __init__.py
- setup.py
Then merge the PR once it's approved.
3. Add a tag "vVERSION" (e.g. v0.4.1) in git to mark the release : "git tag vVERSION -m 'Add tag vVERSION for pypi'"
Push the tag to remote: git push --tags origin main
Then verify that the 'Python release' CI job runs and succeeds.
4. Fill release notes in the tag in github once everything is looking hunky-dory.
5. Open a PR to change the version in __init__.py and setup.py to X.X.X+1.dev0 (e.g. VERSION=0.4.1 -> 0.4.2.dev0).
Then merge the PR once it's approved.
"""
import os
from setuptools import find_packages, setup
REQUIRED_PKGS = [
# We need datasets as a backend
"datasets>=2.0.0",
# We use numpy>=1.17 to have np.random.Generator (Dataset shuffling)
"numpy>=1.17",
# For smart caching dataset processing
"dill",
# For performance gains with apache arrow
"pandas",
# for downloading datasets over HTTPS
"requests>=2.19.0",
# progress bars in download and scripts
"tqdm>=4.62.1",
# for fast hashing
"xxhash",
# for better multiprocessing
"multiprocess",
# to get metadata of optional dependencies such as torch or tensorflow for Python versions that don't have it
"importlib_metadata;python_version<'3.8'",
# to save datasets locally or on any filesystem
# minimum 2021.05.0 to have the AbstractArchiveFileSystem
"fsspec[http]>=2021.05.0",
# To get datasets from the Datasets Hub on huggingface.co
"huggingface-hub>=0.7.0",
# Utilities from PyPA to e.g., compare versions
"packaging",
]
TEMPLATE_REQUIRE = [
# to populate metric template
"cookiecutter",
# for the gradio widget
"gradio>=3.0.0"
]
EVALUATOR_REQUIRE = [
"transformers",
# for bootstrap computations in Evaluator
"scipy>=1.7.1",
]
TESTS_REQUIRE = [
# test dependencies
"absl-py",
"charcut>=1.1.1", # for charcut_mt
"cer>=1.2.0", # for characTER
"nltk", # for NIST and probably others
"pytest",
"pytest-datadir",
"pytest-xdist",
# optional dependencies
"numpy<2.0.0", # tensorflow requires numpy < 2
"tensorflow>=2.3,!=2.6.0,!=2.6.1, <=2.10",
"torch",
# metrics dependencies
"accelerate", # for frugalscore (calls transformers' Trainer)
"bert_score>=0.3.6",
"rouge_score>=0.1.2",
"sacrebleu",
"sacremoses",
"scipy>=1.10.0",
"seqeval",
"scikit-learn",
"jiwer",
"sentencepiece", # for bleurt
"transformers", # for evaluator
"mauve-text",
"trectools",
# to speed up pip backtracking
"toml>=0.10.1",
"requests_file>=1.5.1",
"tldextract>=3.1.0",
"texttable>=1.6.3",
"unidecode>=1.3.4",
"Werkzeug>=1.0.1",
"six~=1.15.0",
]
QUALITY_REQUIRE = ["black~=22.0", "flake8>=3.8.3", "isort>=5.0.0", "pyyaml>=5.3.1"]
EXTRAS_REQUIRE = {
"tensorflow": ["tensorflow>=2.2.0,!=2.6.0,!=2.6.1"],
"tensorflow_gpu": ["tensorflow-gpu>=2.2.0,!=2.6.0,!=2.6.1"],
"torch": ["torch"],
"dev": TESTS_REQUIRE + QUALITY_REQUIRE,
"tests": TESTS_REQUIRE,
"quality": QUALITY_REQUIRE,
"docs": [
# Might need to add doc-builder and some specific deps in the future
"s3fs",
],
"template": TEMPLATE_REQUIRE,
"evaluator": EVALUATOR_REQUIRE
}
setup(
name="evaluate",
version="0.4.4.dev0", # expected format is one of x.y.z.dev0, or x.y.z.rc1 or x.y.z (no to dashes, yes to dots)
description="HuggingFace community-driven open-source library of evaluation",
long_description=open("README.md", encoding="utf-8").read(),
long_description_content_type="text/markdown",
author="HuggingFace Inc.",
author_email="[email protected]",
url="https://github.com/huggingface/evaluate",
download_url="https://github.com/huggingface/evaluate/tags",
license="Apache 2.0",
package_dir={"": "src"},
packages=find_packages("src"),
entry_points={"console_scripts": ["evaluate-cli=evaluate.commands.evaluate_cli:main"]},
install_requires=REQUIRED_PKGS,
extras_require=EXTRAS_REQUIRE,
python_requires=">=3.8.0",
classifiers=[
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
keywords="metrics machine learning evaluate evaluation",
zip_safe=False, # Required for mypy to find the py.typed file
)