
"""simple docstring"""




import re
import string
from collections import Counter

import sacrebleu
import sacremoses
from packaging import version

import datasets


UpperCAmelCase__      :    Any    							= '\n@inproceedings{xu-etal-2016-optimizing,\n    title = {Optimizing Statistical Machine Translation for Text Simplification},\n    authors={Xu, Wei and Napoles, Courtney and Pavlick, Ellie and Chen, Quanze and Callison-Burch, Chris},\n    journal = {Transactions of the Association for Computational Linguistics},\n    volume = {4},\n    year={2016},\n    url = {https://www.aclweb.org/anthology/Q16-1029},\n    pages = {401--415\n},\n@inproceedings{post-2018-call,\n    title = \"A Call for Clarity in Reporting {BLEU} Scores\",\n    author = \"Post, Matt\",\n    booktitle = \"Proceedings of the Third Conference on Machine Translation: Research Papers\",\n    month = oct,\n    year = \"2018\",\n    address = \"Belgium, Brussels\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://www.aclweb.org/anthology/W18-6319\",\n    pages = \"186--191\",\n}\n'

UpperCAmelCase__      :    Union[str, Any]    							= '\\nWIKI_SPLIT is the combination of three metrics SARI, EXACT and SACREBLEU\nIt can be used to evaluate the quality of machine-generated texts.\n'


UpperCAmelCase__      :    Union[str, Any]    							= '\nCalculates sari score (between 0 and 100) given a list of source and predicted\nsentences, and a list of lists of reference sentences. It also computes the BLEU score as well as the exact match score.\nArgs:\n    sources: list of source sentences where each sentence should be a string.\n    predictions: list of predicted sentences where each sentence should be a string.\n    references: list of lists of reference sentences where each sentence should be a string.\nReturns:\n    sari: sari score\n    sacrebleu: sacrebleu score\n    exact: exact score\n\nExamples:\n    >>> sources=[\"About 95 species are currently accepted .\"]\n    >>> predictions=[\"About 95 you now get in .\"]\n    >>> references=[[\"About 95 species are currently known .\"]]\n    >>> wiki_split = datasets.load_metric(\"wiki_split\")\n    >>> results = wiki_split.compute(sources=sources, predictions=predictions, references=references)\n    >>> print(results)\n    {\'sari\': 21.805555555555557, \'sacrebleu\': 14.535768424205482, \'exact\': 0.0}\n'

def lowercase_  (   _snake_case						):





							def remove_articles(_snake_case						):
														SCREAMING_SNAKE_CASE__						:       Dict           =   re.compile(R"""\b(a|an|the)\b"""   ,re.UNICODE						)
														return re.sub(_UpperCAmelCase   ,""" """   ,_UpperCAmelCase						)

							def white_space_fix(_snake_case						):
														return " ".join(text.split()						)

							def remove_punc(_snake_case						):
														SCREAMING_SNAKE_CASE__						:       Dict           =   set(string.punctuation						)
														return "".join(ch for ch in text if ch not in exclude						)

							def lower(_snake_case						):
														return text.lower()

							return white_space_fix(remove_articles(remove_punc(lower(_UpperCAmelCase						)						)						)						)

def lowercase_  (   _snake_case   ,_snake_case						):
							return int(normalize_answer(_UpperCAmelCase						) == normalize_answer(_UpperCAmelCase						)						)

def lowercase_  (   _snake_case   ,_snake_case						):
							SCREAMING_SNAKE_CASE__						:       Tuple           =   [any(compute_exact(_UpperCAmelCase   ,_UpperCAmelCase						) for ref in refs						) for pred, refs in zip(_UpperCAmelCase   ,_UpperCAmelCase						)]
							return (sum(_UpperCAmelCase						) / len(_UpperCAmelCase						)) * 100

def lowercase_  (   _snake_case   ,_snake_case   ,_snake_case   ,_snake_case						):
							SCREAMING_SNAKE_CASE__						:       List[str]           =   [rgram for rgrams in rgramslist for rgram in rgrams]
							SCREAMING_SNAKE_CASE__						:       List[str]           =   Counter(_UpperCAmelCase						)

							SCREAMING_SNAKE_CASE__						:       Any           =   Counter(_UpperCAmelCase						)
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   Counter()
							for sgram, scount in sgramcounter.items():
														SCREAMING_SNAKE_CASE__						:       Dict           =   scount * numref

							SCREAMING_SNAKE_CASE__						:       str           =   Counter(_UpperCAmelCase						)
							SCREAMING_SNAKE_CASE__						:       Dict           =   Counter()
							for cgram, ccount in cgramcounter.items():
														SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   ccount * numref

							# KEEP
							SCREAMING_SNAKE_CASE__						:       Tuple           =   sgramcounter_rep & cgramcounter_rep
							SCREAMING_SNAKE_CASE__						:       Dict           =   keepgramcounter_rep & rgramcounter
							SCREAMING_SNAKE_CASE__						:       Any           =   sgramcounter_rep & rgramcounter

							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   0
							SCREAMING_SNAKE_CASE__						:       Dict           =   0
							for keepgram in keepgramcountergood_rep:
														keeptmpscorea += keepgramcountergood_rep[keepgram] / keepgramcounter_rep[keepgram]
														# Fix an alleged bug [2] in the keep score computation.
														# keeptmpscore2 += keepgramcountergood_rep[keepgram] / keepgramcounterall_rep[keepgram]
														keeptmpscorea += keepgramcountergood_rep[keepgram]
							# Define 0/0=1 instead of 0 to give higher scores for predictions that match
							#      a target exactly.
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   1
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   1
							if len(_UpperCAmelCase						) > 0:
														SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   keeptmpscorea / len(_UpperCAmelCase						)
							if len(_UpperCAmelCase						) > 0:
														# Fix an alleged bug [2] in the keep score computation.
														# keepscore_recall = keeptmpscore2 / len(keepgramcounterall_rep)
														SCREAMING_SNAKE_CASE__						:       Optional[int]           =   keeptmpscorea / sum(keepgramcounterall_rep.values()						)
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   0
							if keepscore_precision > 0 or keepscore_recall > 0:
														SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   2 * keepscore_precision * keepscore_recall / (keepscore_precision + keepscore_recall)

							# DELETION
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   sgramcounter_rep - cgramcounter_rep
							SCREAMING_SNAKE_CASE__						:       List[Any]           =   delgramcounter_rep - rgramcounter
							SCREAMING_SNAKE_CASE__						:       List[Any]           =   sgramcounter_rep - rgramcounter
							SCREAMING_SNAKE_CASE__						:       Dict           =   0
							SCREAMING_SNAKE_CASE__						:       List[str]           =   0
							for delgram in delgramcountergood_rep:
														deltmpscorea += delgramcountergood_rep[delgram] / delgramcounter_rep[delgram]
														deltmpscorea += delgramcountergood_rep[delgram] / delgramcounterall_rep[delgram]
							# Define 0/0=1 instead of 0 to give higher scores for predictions that match
							# a target exactly.
							SCREAMING_SNAKE_CASE__						:       List[Any]           =   1
							if len(_UpperCAmelCase						) > 0:
														SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   deltmpscorea / len(_UpperCAmelCase						)

							# ADDITION
							SCREAMING_SNAKE_CASE__						:       Dict           =   set(_UpperCAmelCase						) - set(_UpperCAmelCase						)
							SCREAMING_SNAKE_CASE__						:       Optional[int]           =   set(_UpperCAmelCase						) & set(_UpperCAmelCase						)
							SCREAMING_SNAKE_CASE__						:       List[str]           =   set(_UpperCAmelCase						) - set(_UpperCAmelCase						)

							SCREAMING_SNAKE_CASE__						:       Tuple           =   0
							for addgram in addgramcountergood:
														addtmpscore += 1

							# Define 0/0=1 instead of 0 to give higher scores for predictions that match
							# a target exactly.
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   1
							SCREAMING_SNAKE_CASE__						:       List[str]           =   1
							if len(_UpperCAmelCase						) > 0:
														SCREAMING_SNAKE_CASE__						:       Dict           =   addtmpscore / len(_UpperCAmelCase						)
							if len(_UpperCAmelCase						) > 0:
														SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   addtmpscore / len(_UpperCAmelCase						)
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   0
							if addscore_precision > 0 or addscore_recall > 0:
														SCREAMING_SNAKE_CASE__						:       Optional[int]           =   2 * addscore_precision * addscore_recall / (addscore_precision + addscore_recall)

							return (keepscore, delscore_precision, addscore)

def lowercase_  (   _snake_case   ,_snake_case   ,_snake_case						):
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   len(_UpperCAmelCase						)

							SCREAMING_SNAKE_CASE__						:       int           =   ssent.split(""" """						)
							SCREAMING_SNAKE_CASE__						:       Dict           =   csent.split(""" """						)
							SCREAMING_SNAKE_CASE__						:       Any           =   []
							SCREAMING_SNAKE_CASE__						:       int           =   []
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   []
							SCREAMING_SNAKE_CASE__						:       str           =   []
							SCREAMING_SNAKE_CASE__						:       str           =   []
							SCREAMING_SNAKE_CASE__						:       str           =   []

							SCREAMING_SNAKE_CASE__						:       Any           =   []
							SCREAMING_SNAKE_CASE__						:       str           =   []
							SCREAMING_SNAKE_CASE__						:       List[Any]           =   []
							SCREAMING_SNAKE_CASE__						:       Tuple           =   []
							for rsent in rsents:
														SCREAMING_SNAKE_CASE__						:       List[Any]           =   rsent.split(""" """						)
														SCREAMING_SNAKE_CASE__						:       Tuple           =   []
														SCREAMING_SNAKE_CASE__						:       Any           =   []
														SCREAMING_SNAKE_CASE__						:       List[Any]           =   []
														ragramslist.append(_UpperCAmelCase						)
														for i in range(0   ,len(_UpperCAmelCase						) - 1						):
																					if i < len(_UpperCAmelCase						) - 1:
																												SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   ragrams[i] + ''' ''' + ragrams[i + 1]
																												ragrams.append(_UpperCAmelCase						)
																					if i < len(_UpperCAmelCase						) - 2:
																												SCREAMING_SNAKE_CASE__						:       Any           =   ragrams[i] + ''' ''' + ragrams[i + 1] + ''' ''' + ragrams[i + 2]
																												ragrams.append(_UpperCAmelCase						)
																					if i < len(_UpperCAmelCase						) - 3:
																												SCREAMING_SNAKE_CASE__						:       List[str]           =   ragrams[i] + ''' ''' + ragrams[i + 1] + ''' ''' + ragrams[i + 2] + ''' ''' + ragrams[i + 3]
																												ragrams.append(_UpperCAmelCase						)
														ragramslist.append(_UpperCAmelCase						)
														ragramslist.append(_UpperCAmelCase						)
														ragramslist.append(_UpperCAmelCase						)

							for i in range(0   ,len(_UpperCAmelCase						) - 1						):
														if i < len(_UpperCAmelCase						) - 1:
																					SCREAMING_SNAKE_CASE__						:       List[str]           =   sagrams[i] + ''' ''' + sagrams[i + 1]
																					sagrams.append(_UpperCAmelCase						)
														if i < len(_UpperCAmelCase						) - 2:
																					SCREAMING_SNAKE_CASE__						:       Tuple           =   sagrams[i] + ''' ''' + sagrams[i + 1] + ''' ''' + sagrams[i + 2]
																					sagrams.append(_UpperCAmelCase						)
														if i < len(_UpperCAmelCase						) - 3:
																					SCREAMING_SNAKE_CASE__						:       Tuple           =   sagrams[i] + ''' ''' + sagrams[i + 1] + ''' ''' + sagrams[i + 2] + ''' ''' + sagrams[i + 3]
																					sagrams.append(_UpperCAmelCase						)

							for i in range(0   ,len(_UpperCAmelCase						) - 1						):
														if i < len(_UpperCAmelCase						) - 1:
																					SCREAMING_SNAKE_CASE__						:       Any           =   cagrams[i] + ''' ''' + cagrams[i + 1]
																					cagrams.append(_UpperCAmelCase						)
														if i < len(_UpperCAmelCase						) - 2:
																					SCREAMING_SNAKE_CASE__						:       Any           =   cagrams[i] + ''' ''' + cagrams[i + 1] + ''' ''' + cagrams[i + 2]
																					cagrams.append(_UpperCAmelCase						)
														if i < len(_UpperCAmelCase						) - 3:
																					SCREAMING_SNAKE_CASE__						:       Any           =   cagrams[i] + ''' ''' + cagrams[i + 1] + ''' ''' + cagrams[i + 2] + ''' ''' + cagrams[i + 3]
																					cagrams.append(_UpperCAmelCase						)

							(SCREAMING_SNAKE_CASE__)						:       List[str]           =   SARIngram(_UpperCAmelCase   ,_UpperCAmelCase   ,_UpperCAmelCase   ,_UpperCAmelCase						)
							(SCREAMING_SNAKE_CASE__)						:       int           =   SARIngram(_UpperCAmelCase   ,_UpperCAmelCase   ,_UpperCAmelCase   ,_UpperCAmelCase						)
							(SCREAMING_SNAKE_CASE__)						:       Union[str, Any]           =   SARIngram(_UpperCAmelCase   ,_UpperCAmelCase   ,_UpperCAmelCase   ,_UpperCAmelCase						)
							(SCREAMING_SNAKE_CASE__)						:       Optional[int]           =   SARIngram(_UpperCAmelCase   ,_UpperCAmelCase   ,_UpperCAmelCase   ,_UpperCAmelCase						)
							SCREAMING_SNAKE_CASE__						:       Tuple           =   sum([keepascore, keepascore, keepascore, keepascore]						) / 4
							SCREAMING_SNAKE_CASE__						:       List[str]           =   sum([delascore, delascore, delascore, delascore]						) / 4
							SCREAMING_SNAKE_CASE__						:       str           =   sum([addascore, addascore, addascore, addascore]						) / 4
							SCREAMING_SNAKE_CASE__						:       Optional[int]           =   (avgkeepscore + avgdelscore + avgaddscore) / 3
							return finalscore

def lowercase_  (   _snake_case   ,_snake_case = True   ,_snake_case = "13a"   ,_snake_case = True						):





							if lowercase:
														SCREAMING_SNAKE_CASE__						:       List[str]           =   sentence.lower()

							if tokenizer in ["13a", "intl"]:
														if version.parse(sacrebleu.__version__						).major >= 2:
																					SCREAMING_SNAKE_CASE__						:       List[str]           =   sacrebleu.metrics.bleu._get_tokenizer(_UpperCAmelCase						)()(_UpperCAmelCase						)
														else:
																					SCREAMING_SNAKE_CASE__						:       List[str]           =   sacrebleu.TOKENIZERS[tokenizer]()(_UpperCAmelCase						)
							elif tokenizer == "moses":
														SCREAMING_SNAKE_CASE__						:       Optional[int]           =   sacremoses.MosesTokenizer().tokenize(_UpperCAmelCase   ,return_str=_UpperCAmelCase   ,escape=_UpperCAmelCase						)
							elif tokenizer == "penn":
														SCREAMING_SNAKE_CASE__						:       Dict           =   sacremoses.MosesTokenizer().penn_tokenize(_UpperCAmelCase   ,return_str=_UpperCAmelCase						)
							else:
														SCREAMING_SNAKE_CASE__						:       List[str]           =   sentence

							if not return_str:
														SCREAMING_SNAKE_CASE__						:       List[str]           =   normalized_sent.split()

							return normalized_sent

def lowercase_  (   _snake_case   ,_snake_case   ,_snake_case						):





							if not (len(_UpperCAmelCase						) == len(_UpperCAmelCase						) == len(_UpperCAmelCase						)):
														raise ValueError("""Sources length must match predictions and references lengths."""						)
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   0
							for src, pred, refs in zip(_UpperCAmelCase   ,_UpperCAmelCase   ,_UpperCAmelCase						):
														sari_score += SARIsent(normalize(_UpperCAmelCase						)   ,normalize(_UpperCAmelCase						)   ,[normalize(_UpperCAmelCase						) for sent in refs]						)
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   sari_score / len(_UpperCAmelCase						)
							return 100 * sari_score

def lowercase_  (   _snake_case   ,_snake_case   ,_snake_case="exp"   ,_snake_case=None   ,_snake_case=False   ,_snake_case=False   ,_snake_case=False   ,):
							SCREAMING_SNAKE_CASE__						:       Tuple           =   len(references[0]						)
							if any(len(_UpperCAmelCase						) != references_per_prediction for refs in references						):
														raise ValueError("""Sacrebleu requires the same number of references for each prediction"""						)
							SCREAMING_SNAKE_CASE__						:       Dict           =   [[refs[i] for refs in references] for i in range(_UpperCAmelCase						)]
							SCREAMING_SNAKE_CASE__						:       Optional[int]           =   sacrebleu.corpus_bleu(
							    _UpperCAmelCase   ,_UpperCAmelCase   ,smooth_method=_UpperCAmelCase   ,smooth_value=_UpperCAmelCase   ,force=_UpperCAmelCase   ,lowercase=_UpperCAmelCase   ,use_effective_order=_UpperCAmelCase   ,)
							return output.score



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


				"""simple docstring"""



				def 	__magic_name__    (self    )					->		List[str]:



											"""simple docstring"""




											return datasets.MetricInfo(
											    description=_DESCRIPTION   ,       citation=_CITATION   ,       inputs_description=_KWARGS_DESCRIPTION   ,       features=datasets.Features(
											        {
											            """predictions""": datasets.Value("""string"""   ,       id="""sequence"""    ),
											            """references""": datasets.Sequence(datasets.Value("""string"""   ,       id="""sequence"""    )   ,       id="""references"""    ),
											        }    )   ,       codebase_urls=[
											        """https://github.com/huggingface/transformers/blob/master/src/transformers/data/metrics/squad_metrics.py""",
											        """https://github.com/cocoxu/simplification/blob/master/SARI.py""",
											        """https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/utils/sari_hook.py""",
											        """https://github.com/mjpost/sacreBLEU""",
											    ]   ,       reference_urls=[
											        """https://www.aclweb.org/anthology/Q16-1029.pdf""",
											        """https://github.com/mjpost/sacreBLEU""",
											        """https://en.wikipedia.org/wiki/BLEU""",
											        """https://towardsdatascience.com/evaluating-text-output-in-nlp-bleu-at-your-own-risk-e8609665a213""",
											    ]   ,       )



				def 	__magic_name__    (self   ,       SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )					->		Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Tuple           =   {}
											result.update({"""sari""": compute_sari(sources=a_   ,       predictions=a_   ,       references=a_    )}    )
											result.update({"""sacrebleu""": compute_sacrebleu(predictions=a_   ,       references=a_    )}    )
											result.update({"""exact""": compute_em(predictions=a_   ,       references=a_    )}    )
											return result









def        a						(      _UpperCAmelCase							:					Any						):







		'''simple docstring'''





		__UpperCAmelCase    :     Any													=	0
		__UpperCAmelCase    :     str													=	len(_UpperCAmelCase						)

		for i in range(n - 1						):
				for j in range(i + 1 ,   _UpperCAmelCase						):
						if arr[i] > arr[j]:
								num_inversions += 1

		return num_inversions

def        a						(      _UpperCAmelCase							:					str						):







		'''simple docstring'''





		if len(_UpperCAmelCase						) <= 1:
				return arr, 0
		__UpperCAmelCase    :     Dict													=	len(_UpperCAmelCase						) // 2
		__UpperCAmelCase    :     Union[str, Any]													=	arr[0:mid]
		__UpperCAmelCase    :     Optional[Any]													=	arr[mid:]

		__UpperCAmelCase							,					__UpperCAmelCase    :     Tuple													=	count_inversions_recursive(_UpperCAmelCase						)
		__UpperCAmelCase							,					__UpperCAmelCase    :     Optional[Any]													=	count_inversions_recursive(_UpperCAmelCase						)
		__UpperCAmelCase							,					__UpperCAmelCase    :     int													=	_count_cross_inversions(_UpperCAmelCase ,   _UpperCAmelCase						)

		__UpperCAmelCase    :     List[str]													=	inversion_p + inversions_q + cross_inversions
		return c, num_inversions

def        a						(      _UpperCAmelCase							:					List[str] ,   _UpperCAmelCase							:					Any						):







		'''simple docstring'''





		__UpperCAmelCase    :     List[Any]													=	[]
		__UpperCAmelCase    :     Any													=	0
		while i < len(_UpperCAmelCase						) and j < len(_UpperCAmelCase						):
				if p[i] > q[j]:
						# if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
						# These are all inversions. The claim emerges from the
						# property that P is sorted.
						num_inversion += len(_UpperCAmelCase						) - i
						r.append(q[j]						)
						j += 1
				else:
						r.append(p[i]						)
						i += 1

		if i < len(_UpperCAmelCase						):
				r.extend(p[i:]						)
		else:
				r.extend(q[j:]						)

		return r, num_inversion

def        a						(      ):







		'''simple docstring'''





		__UpperCAmelCase    :     Optional[Any]													=	[10, 2, 1, 5, 5, 2, 11]

		# this arr has 8 inversions:
		# (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

		__UpperCAmelCase    :     List[str]													=	count_inversions_bf(_UpperCAmelCase						)
		__UpperCAmelCase							,					__UpperCAmelCase    :     Tuple													=	count_inversions_recursive(_UpperCAmelCase						)

		assert num_inversions_bf == num_inversions_recursive == 8

		print('''number of inversions = ''' ,   _UpperCAmelCase						)

		# testing an array with zero inversion (a sorted arr_1)

		arr_a.sort()
		__UpperCAmelCase    :     Any													=	count_inversions_bf(_UpperCAmelCase						)
		__UpperCAmelCase							,					__UpperCAmelCase    :     int													=	count_inversions_recursive(_UpperCAmelCase						)

		assert num_inversions_bf == num_inversions_recursive == 0
		print('''number of inversions = ''' ,   _UpperCAmelCase						)

		# an empty list should also have zero inversions
		__UpperCAmelCase    :     Tuple													=	[]
		__UpperCAmelCase    :     Union[str, Any]													=	count_inversions_bf(_UpperCAmelCase						)
		__UpperCAmelCase							,					__UpperCAmelCase    :     int													=	count_inversions_recursive(_UpperCAmelCase						)

		assert num_inversions_bf == num_inversions_recursive == 0
		print('''number of inversions = ''' ,   _UpperCAmelCase						)


if __name__ == "__main__":
				main()





