


'''simple docstring'''







import numpy as np
from nltk.translate import meteor_score

import datasets
from datasets.config import importlib_metadata, version


A__:    Dict					    =       version.parse(importlib_metadata.version('''nltk'''))
if NLTK_VERSION >= version.Version('''3.6.4'''):
   from nltk import word_tokenize


A__:    Union[str, Any]					    =       '''\\n@inproceedings{banarjee2005,\n  title     = {{METEOR}: An Automatic Metric for {MT} Evaluation with Improved Correlation with Human Judgments},\n  author    = {Banerjee, Satanjeev  and Lavie, Alon},\n  booktitle = {Proceedings of the {ACL} Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization},\n  month     = jun,\n  year      = {2005},\n  address   = {Ann Arbor, Michigan},\n  publisher = {Association for Computational Linguistics},\n  url       = {https://www.aclweb.org/anthology/W05-0909},\n  pages     = {65--72},\n}\n'''

A__:    List[str]					    =       '''\\nMETEOR, an automatic metric for machine translation evaluation\nthat is based on a generalized concept of unigram matching between the\nmachine-produced translation and human-produced reference translations.\nUnigrams can be matched based on their surface forms, stemmed forms,\nand meanings; furthermore, METEOR can be easily extended to include more\nadvanced matching strategies. Once all generalized unigram matches\nbetween the two strings have been found, METEOR computes a score for\nthis matching using a combination of unigram-precision, unigram-recall, and\na measure of fragmentation that is designed to directly capture how\nwell-ordered the matched words in the machine translation are in relation\nto the reference.\n\nMETEOR gets an R correlation value of 0.347 with human evaluation on the Arabic\ndata and 0.331 on the Chinese data. This is shown to be an improvement on\nusing simply unigram-precision, unigram-recall and their harmonic F1\ncombination.\n'''

A__:    Tuple					    =       '''\nComputes METEOR score of translated segments against one or more references.\nArgs:\n    predictions: list of predictions to score. Each prediction\n        should be a string with tokens separated by spaces.\n    references: list of reference for each prediction. Each\n        reference should be a string with tokens separated by spaces.\n    alpha: Parameter for controlling relative weights of precision and recall. default: 0.9\n    beta: Parameter for controlling shape of penalty as a function of fragmentation. default: 3\n    gamma: Relative weight assigned to fragmentation penalty. default: 0.5\nReturns:\n    \'meteor\': meteor score.\nExamples:\n\n    >>> meteor = datasets.load_metric(\'meteor\')\n    >>> predictions = ["It is a guide to action which ensures that the military always obeys the commands of the party"]\n    >>> references = ["It is a guide to action that ensures that the military will forever heed Party commands"]\n    >>> results = meteor.compute(predictions=predictions, references=references)\n    >>> print(round(results["meteor"], 4))\n    0.6944\n'''







@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION ,     _KWARGS_DESCRIPTION      )
class A__       (						datasets.Metric      ):






      def __UpperCAmelCase       ( self			:Optional[int]	)       ->					Union[str, Any]:




             '''simple docstring'''
             return datasets.MetricInfo(
                 description=_DESCRIPTION     ,						citation=_CITATION     ,						inputs_description=_KWARGS_DESCRIPTION     ,						features=datasets.Features(
                     {
                         """predictions""": datasets.Value("""string"""     ,						id="""sequence"""	),
                         """references""": datasets.Value("""string"""     ,						id="""sequence"""	),
                     }	)     ,						codebase_urls=["""https://github.com/nltk/nltk/blob/develop/nltk/translate/meteor_score.py"""]     ,						reference_urls=[
                     """https://www.nltk.org/api/nltk.translate.html#module-nltk.translate.meteor_score""",
                     """https://en.wikipedia.org/wiki/METEOR""",
                 ]     ,						)






      def __UpperCAmelCase       ( self			:Optional[Any]     ,						SCREAMING_SNAKE_CASE			:Any	)       ->					List[Any]:




             '''simple docstring'''
             import nltk

             nltk.download("""wordnet"""	)
             if NLTK_VERSION >= version.Version("""3.6.5"""	):
                    nltk.download("""punkt"""	)
             if NLTK_VERSION >= version.Version("""3.6.6"""	):
                    nltk.download("""omw-1.4"""	)






      def __UpperCAmelCase       ( self			:Dict     ,						SCREAMING_SNAKE_CASE			:List[Any]     ,						SCREAMING_SNAKE_CASE			:List[Any]     ,						SCREAMING_SNAKE_CASE			:List[str]=0.9     ,						SCREAMING_SNAKE_CASE			:Tuple=3     ,						SCREAMING_SNAKE_CASE			:str=0.5	)       ->					List[str]:




             '''simple docstring'''
             if NLTK_VERSION >= version.Version("""3.6.5"""	):
                    _a    : Any     					=[
                        meteor_score.single_meteor_score(
                            word_tokenize(_UpperCamelCase	)     ,						word_tokenize(_UpperCamelCase	)     ,						alpha=_UpperCamelCase     ,						beta=_UpperCamelCase     ,						gamma=_UpperCamelCase	)
                        for ref, pred in zip(_UpperCamelCase     ,						_UpperCamelCase	)
                    ]
             else:
                    _a    : Dict     					=[
                        meteor_score.single_meteor_score(_UpperCamelCase     ,						_UpperCamelCase     ,						alpha=_UpperCamelCase     ,						beta=_UpperCamelCase     ,						gamma=_UpperCamelCase	)
                        for ref, pred in zip(_UpperCamelCase     ,						_UpperCamelCase	)
                    ]

             return {"meteor": np.mean(_UpperCamelCase	)}










import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


__UpperCAmelCase								=						importlib.util.find_spec('s3fs') is not None

if _has_safs:
		from .safilesystem import SaFileSystem  # noqa: F401

__UpperCAmelCase								=						[
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
		if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
				warnings.warn(F'A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.')
		fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)




def      lowercase__      (     __snake_case    :							str  ):


					'''simple docstring'''


					if "://" in dataset_path:
										UpperCAmelCase_    :      int            =						dataset_path.split('://'  )[1]
					return dataset_path




def      lowercase__      (     __snake_case    :							fsspec.AbstractFileSystem  ):


					'''simple docstring'''


					if fs is not None and fs.protocol != "file":
										return True
					else:
										return False




def      lowercase__      (     __snake_case    :							fsspec.AbstractFileSystem     ,       __snake_case    :							str     ,       __snake_case    :							str  ):


					'''simple docstring'''


					UpperCAmelCase_    :      List[str]            =						not is_remote_filesystem(__snake_case  )
					if is_local:
										# LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
										shutil.move(fs._strip_protocol(__snake_case  )     ,       fs._strip_protocol(__snake_case  )  )
					else:
										fs.mv(__snake_case     ,       __snake_case     ,       recursive=__snake_case  )






def      lowercase__      (     ):


					'''simple docstring'''


					if hasattr(fsspec.asyn     ,       'reset_lock'  ):
										# for future fsspec>2022.05.0
										fsspec.asyn.reset_lock()
					else:
										UpperCAmelCase_    :      Optional[Any]            =						None
										UpperCAmelCase_    :      Union[str, Any]            =						None
										UpperCAmelCase_    :      int            =						threading.Lock()






