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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="0.4.7.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="leandro@huggingface.co",

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

)