
# Imports
import numpy as np



class    _snake_case :


 def __init__(       self       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None):


   '''simple docstring'''




   self.set_matricies(red=SCREAMING_SNAKE_CASE_       ,	green=SCREAMING_SNAKE_CASE_       ,	blue=SCREAMING_SNAKE_CASE_       ,	red_edge=SCREAMING_SNAKE_CASE_       ,	nir=SCREAMING_SNAKE_CASE_)


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None):


   '''simple docstring'''




   if red is not None:
     lowercase__	: List[str]     		=   red
   if green is not None:
     lowercase__	: Union[str, Any]     		=   green
   if blue is not None:
     lowercase__	: int     		=   blue
   if red_edge is not None:
     lowercase__	: Optional[Any]     		=   red_edge
   if nir is not None:
     lowercase__	: Optional[Any]     		=   nir
   return True


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_=""       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None):


   '''simple docstring'''




   self.set_matricies(red=SCREAMING_SNAKE_CASE_       ,	green=SCREAMING_SNAKE_CASE_       ,	blue=SCREAMING_SNAKE_CASE_       ,	red_edge=SCREAMING_SNAKE_CASE_       ,	nir=SCREAMING_SNAKE_CASE_)
   lowercase__	: Dict     		=   {
       """ARVI2""": self.arvaa,
       """CCCI""": self.ccci,
       """CVI""": self.cvi,
       """GLI""": self.gli,
       """NDVI""": self.ndvi,
       """BNDVI""": self.bndvi,
       """redEdgeNDVI""": self.red_edge_ndvi,
       """GNDVI""": self.gndvi,
       """GBNDVI""": self.gbndvi,
       """GRNDVI""": self.grndvi,
       """RBNDVI""": self.rbndvi,
       """PNDVI""": self.pndvi,
       """ATSAVI""": self.atsavi,
       """BWDRVI""": self.bwdrvi,
       """CIgreen""": self.ci_green,
       """CIrededge""": self.ci_rededge,
       """CI""": self.ci,
       """CTVI""": self.ctvi,
       """GDVI""": self.gdvi,
       """EVI""": self.evi,
       """GEMI""": self.gemi,
       """GOSAVI""": self.gosavi,
       """GSAVI""": self.gsavi,
       """Hue""": self.hue,
       """IVI""": self.ivi,
       """IPVI""": self.ipvi,
       """I""": self.i,
       """RVI""": self.rvi,
       """MRVI""": self.mrvi,
       """MSAVI""": self.m_savi,
       """NormG""": self.norm_g,
       """NormNIR""": self.norm_nir,
       """NormR""": self.norm_r,
       """NGRDI""": self.ngrdi,
       """RI""": self.ri,
       """S""": self.s,
       """IF""": self._if,
       """DVI""": self.dvi,
       """TVI""": self.tvi,
       """NDRE""": self.ndre,
   }

   try:
     return funcs[index]()
   except KeyError:
     print("""Index not in the list!""")
     return False


 def   lowercase__  (       self):


   '''simple docstring'''




   return -0.1_8 + (1.1_7 * ((self.nir - self.red) / (self.nir + self.red)))


 def   lowercase__  (       self):


   '''simple docstring'''




   return ((self.nir - self.redEdge) / (self.nir + self.redEdge)) / (
       (self.nir - self.red) / (self.nir + self.red)
   )


 def   lowercase__  (       self):


   '''simple docstring'''




   return self.nir * (self.red / (self.green**2))


 def   lowercase__  (       self):


   '''simple docstring'''




   return (2 * self.green - self.red - self.blue) / (
       2 * self.green + self.red + self.blue
   )


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir - self.red) / (self.nir + self.red)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir - self.blue) / (self.nir + self.blue)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.redEdge - self.red) / (self.redEdge + self.red)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir - self.green) / (self.nir + self.green)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir - (self.green + self.blue)) / (
       self.nir + (self.green + self.blue)
   )


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir - (self.green + self.red)) / (
       self.nir + (self.green + self.red)
   )


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir - (self.blue + self.red)) / (self.nir + (self.blue + self.red))


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir - (self.green + self.red + self.blue)) / (
       self.nir + (self.green + self.red + self.blue)
   )


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_=0.0_8       ,	SCREAMING_SNAKE_CASE_=1.2_2       ,	SCREAMING_SNAKE_CASE_=0.0_3):


   '''simple docstring'''




   return a * (
       (self.nir - a * self.red - b)
       / (a * self.nir + self.red - a * b + x * (1 + a**2))
   )


 def   lowercase__  (       self):


   '''simple docstring'''




   return (0.1 * self.nir - self.blue) / (0.1 * self.nir + self.blue)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir / self.green) - 1


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir / self.redEdge) - 1


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.red - self.blue) / self.red


 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: int     		=   self.ndvi()
   return ((ndvi + 0.5) / (abs(ndvi + 0.5))) * (abs(ndvi + 0.5) ** (1 / 2))


 def   lowercase__  (       self):


   '''simple docstring'''




   return self.nir - self.green


 def   lowercase__  (       self):


   '''simple docstring'''




   return 2.5 * (
       (self.nir - self.red) / (self.nir + 6 * self.red - 7.5 * self.blue + 1)
   )


 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: Union[str, Any]     		=   (2 * (self.nir**2 - self.red**2) + 1.5 * self.nir + 0.5 * self.red) / (
       self.nir + self.red + 0.5
   )
   return n * (1 - 0.2_5 * n) - (self.red - 0.1_2_5) / (1 - self.red)


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_=0.1_6):


   '''simple docstring'''




   return (self.nir - self.green) / (self.nir + self.green + y)


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_=0.5):


   '''simple docstring'''




   return ((self.nir - self.green) / (self.nir + self.green + n)) * (1 + n)


 def   lowercase__  (       self):


   '''simple docstring'''




   return np.arctan(
       ((2 * self.red - self.green - self.blue) / 3_0.5) * (self.green - self.blue))


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_=None       ,	SCREAMING_SNAKE_CASE_=None):


   '''simple docstring'''




   return (self.nir - b) / (a * self.red)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir / ((self.nir + self.red) / 2)) * (self.ndvi() + 1)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.red + self.green + self.blue) / 3_0.5


 def   lowercase__  (       self):


   '''simple docstring'''




   return self.nir / self.red


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.rvi() - 1) / (self.rvi() + 1)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (
       (2 * self.nir + 1)
       - ((2 * self.nir + 1) ** 2 - 8 * (self.nir - self.red)) ** (1 / 2)
   ) / 2


 def   lowercase__  (       self):


   '''simple docstring'''




   return self.green / (self.nir + self.red + self.green)


 def   lowercase__  (       self):


   '''simple docstring'''




   return self.nir / (self.nir + self.red + self.green)


 def   lowercase__  (       self):


   '''simple docstring'''




   return self.red / (self.nir + self.red + self.green)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.green - self.red) / (self.green + self.red)


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.red - self.green) / (self.red + self.green)


 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: Tuple     		=   np.max([np.max(self.red), np.max(self.green), np.max(self.blue)])
   lowercase__	: Dict     		=   np.min([np.min(self.red), np.min(self.green), np.min(self.blue)])
   return (max_value - min_value) / max_value


 def   lowercase__  (       self):


   '''simple docstring'''




   return (2 * self.red - self.green - self.blue) / (self.green - self.blue)


 def   lowercase__  (       self):


   '''simple docstring'''




   return self.nir / self.red


 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.ndvi() + 0.5) ** (1 / 2)



 def   lowercase__  (       self):


   '''simple docstring'''




   return (self.nir - self.redEdge) / (self.nir + self.redEdge)







"""simple docstring"""




import re
import string
from collections import Counter

import sacrebleu
import sacremoses
from packaging import version

import datasets


__lowerCAmelCase     :				Optional[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"

__lowerCAmelCase     :				str    				=    "\\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"


__lowerCAmelCase     :				int    				=    "\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 				_UpperCAmelCase		(							lowerCamelCase__  ):





		"""simple docstring"""




		def remove_articles(lowerCamelCase__  ):
				lowerCAmelCase__   = re.compile(r"""\b(a|an|the)\b"""      ,	re.UNICODE  )
				return re.sub(lowerCamelCase__      ,	""" """      ,	lowerCamelCase__  )

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

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

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

		return white_space_fix(remove_articles(remove_punc(lower(lowerCamelCase__  )  )  )  )







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




		return int(normalize_answer(lowerCamelCase__  ) == normalize_answer(lowerCamelCase__  )  )







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




		lowerCAmelCase__   = [any(compute_exact(lowerCamelCase__      ,	lowerCamelCase__  ) for ref in refs  ) for pred, refs in zip(lowerCamelCase__      ,	lowerCamelCase__  )]
		return (sum(lowerCamelCase__  ) / len(lowerCamelCase__  )) * 100







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




		lowerCAmelCase__   = [rgram for rgrams in rgramslist for rgram in rgrams]
		lowerCAmelCase__   = Counter(lowerCamelCase__  )

		lowerCAmelCase__   = Counter(lowerCamelCase__  )
		lowerCAmelCase__   = Counter()
		for sgram, scount in sgramcounter.items():
				lowerCAmelCase__   = scount * numref

		lowerCAmelCase__   = Counter(lowerCamelCase__  )
		lowerCAmelCase__   = Counter()
		for cgram, ccount in cgramcounter.items():
				lowerCAmelCase__   = ccount * numref

		# KEEP
		lowerCAmelCase__   = sgramcounter_rep & cgramcounter_rep
		lowerCAmelCase__   = keepgramcounter_rep & rgramcounter
		lowerCAmelCase__   = sgramcounter_rep & rgramcounter

		lowerCAmelCase__   = 0
		lowerCAmelCase__   = 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.
		lowerCAmelCase__   = 1
		lowerCAmelCase__   = 1
		if len(lowerCamelCase__  ) > 0:
				lowerCAmelCase__   = keeptmpscorea / len(lowerCamelCase__  )
		if len(lowerCamelCase__  ) > 0:
				# Fix an alleged bug [2] in the keep score computation.
				# keepscore_recall = keeptmpscore2 / len(keepgramcounterall_rep)
				lowerCAmelCase__   = keeptmpscorea / sum(keepgramcounterall_rep.values()  )
		lowerCAmelCase__   = 0
		if keepscore_precision > 0 or keepscore_recall > 0:
				lowerCAmelCase__   = 2 * keepscore_precision * keepscore_recall / (keepscore_precision + keepscore_recall)

		# DELETION
		lowerCAmelCase__   = sgramcounter_rep - cgramcounter_rep
		lowerCAmelCase__   = delgramcounter_rep - rgramcounter
		lowerCAmelCase__   = sgramcounter_rep - rgramcounter
		lowerCAmelCase__   = 0
		lowerCAmelCase__   = 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.
		lowerCAmelCase__   = 1
		if len(lowerCamelCase__  ) > 0:
				lowerCAmelCase__   = deltmpscorea / len(lowerCamelCase__  )

		# ADDITION
		lowerCAmelCase__   = set(lowerCamelCase__  ) - set(lowerCamelCase__  )
		lowerCAmelCase__   = set(lowerCamelCase__  ) & set(lowerCamelCase__  )
		lowerCAmelCase__   = set(lowerCamelCase__  ) - set(lowerCamelCase__  )

		lowerCAmelCase__   = 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.
		lowerCAmelCase__   = 1
		lowerCAmelCase__   = 1
		if len(lowerCamelCase__  ) > 0:
				lowerCAmelCase__   = addtmpscore / len(lowerCamelCase__  )
		if len(lowerCamelCase__  ) > 0:
				lowerCAmelCase__   = addtmpscore / len(lowerCamelCase__  )
		lowerCAmelCase__   = 0
		if addscore_precision > 0 or addscore_recall > 0:
				lowerCAmelCase__   = 2 * addscore_precision * addscore_recall / (addscore_precision + addscore_recall)

		return (keepscore, delscore_precision, addscore)







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




		lowerCAmelCase__   = len(lowerCamelCase__  )

		lowerCAmelCase__   = ssent.split(""" """  )
		lowerCAmelCase__   = csent.split(""" """  )
		lowerCAmelCase__   = []
		lowerCAmelCase__   = []
		lowerCAmelCase__   = []
		lowerCAmelCase__   = []
		lowerCAmelCase__   = []
		lowerCAmelCase__   = []

		lowerCAmelCase__   = []
		lowerCAmelCase__   = []
		lowerCAmelCase__   = []
		lowerCAmelCase__   = []
		for rsent in rsents:
				lowerCAmelCase__   = rsent.split(""" """  )
				lowerCAmelCase__   = []
				lowerCAmelCase__   = []
				lowerCAmelCase__   = []
				ragramslist.append(lowerCamelCase__  )
				for i in range(0      ,	len(lowerCamelCase__  ) - 1  ):
						if i < len(lowerCamelCase__  ) - 1:
								lowerCAmelCase__   = ragrams[i] + """ """ + ragrams[i + 1]
								ragrams.append(lowerCamelCase__  )
						if i < len(lowerCamelCase__  ) - 2:
								lowerCAmelCase__   = ragrams[i] + """ """ + ragrams[i + 1] + """ """ + ragrams[i + 2]
								ragrams.append(lowerCamelCase__  )
						if i < len(lowerCamelCase__  ) - 3:
								lowerCAmelCase__   = ragrams[i] + """ """ + ragrams[i + 1] + """ """ + ragrams[i + 2] + """ """ + ragrams[i + 3]
								ragrams.append(lowerCamelCase__  )
				ragramslist.append(lowerCamelCase__  )
				ragramslist.append(lowerCamelCase__  )
				ragramslist.append(lowerCamelCase__  )

		for i in range(0      ,	len(lowerCamelCase__  ) - 1  ):
				if i < len(lowerCamelCase__  ) - 1:
						lowerCAmelCase__   = sagrams[i] + """ """ + sagrams[i + 1]
						sagrams.append(lowerCamelCase__  )
				if i < len(lowerCamelCase__  ) - 2:
						lowerCAmelCase__   = sagrams[i] + """ """ + sagrams[i + 1] + """ """ + sagrams[i + 2]
						sagrams.append(lowerCamelCase__  )
				if i < len(lowerCamelCase__  ) - 3:
						lowerCAmelCase__   = sagrams[i] + """ """ + sagrams[i + 1] + """ """ + sagrams[i + 2] + """ """ + sagrams[i + 3]
						sagrams.append(lowerCamelCase__  )

		for i in range(0      ,	len(lowerCamelCase__  ) - 1  ):
				if i < len(lowerCamelCase__  ) - 1:
						lowerCAmelCase__   = cagrams[i] + """ """ + cagrams[i + 1]
						cagrams.append(lowerCamelCase__  )
				if i < len(lowerCamelCase__  ) - 2:
						lowerCAmelCase__   = cagrams[i] + """ """ + cagrams[i + 1] + """ """ + cagrams[i + 2]
						cagrams.append(lowerCamelCase__  )
				if i < len(lowerCamelCase__  ) - 3:
						lowerCAmelCase__   = cagrams[i] + """ """ + cagrams[i + 1] + """ """ + cagrams[i + 2] + """ """ + cagrams[i + 3]
						cagrams.append(lowerCamelCase__  )

		((lowerCAmelCase__) ,       (lowerCAmelCase__) ,       (lowerCAmelCase__))   = SARIngram(lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__  )
		((lowerCAmelCase__) ,       (lowerCAmelCase__) ,       (lowerCAmelCase__))   = SARIngram(lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__  )
		((lowerCAmelCase__) ,       (lowerCAmelCase__) ,       (lowerCAmelCase__))   = SARIngram(lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__  )
		((lowerCAmelCase__) ,       (lowerCAmelCase__) ,       (lowerCAmelCase__))   = SARIngram(lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__  )
		lowerCAmelCase__   = sum([keepascore, keepascore, keepascore, keepascore]  ) / 4
		lowerCAmelCase__   = sum([delascore, delascore, delascore, delascore]  ) / 4
		lowerCAmelCase__   = sum([addascore, addascore, addascore, addascore]  ) / 4
		lowerCAmelCase__   = (avgkeepscore + avgdelscore + avgaddscore) / 3
		return finalscore







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__ = True      ,	lowerCamelCase__ = "13a"      ,	lowerCamelCase__ = True  ):





		"""simple docstring"""




		if lowercase:
				lowerCAmelCase__   = sentence.lower()

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

		if not return_str:
				lowerCAmelCase__   = normalized_sent.split()

		return normalized_sent







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




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







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__      ,	lowerCamelCase__="exp"      ,	lowerCamelCase__=None      ,	lowerCamelCase__=False      ,	lowerCamelCase__=False      ,	lowerCamelCase__=False      ,	):





		"""simple docstring"""




		lowerCAmelCase__   = len(references[0]  )
		if any(len(lowerCamelCase__  ) != references_per_prediction for refs in references  ):
				raise ValueError("""Sacrebleu requires the same number of references for each prediction"""  )
		lowerCAmelCase__   = [[refs[i] for refs in references] for i in range(lowerCamelCase__  )]
		lowerCAmelCase__   = sacrebleu.corpus_bleu(
		    lowerCamelCase__      ,	lowerCamelCase__      ,	smooth_method=lowerCamelCase__      ,	smooth_value=lowerCamelCase__      ,	force=lowerCamelCase__      ,	lowercase=lowerCamelCase__      ,	use_effective_order=lowerCamelCase__      ,	)
		return output.score






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




					def     _SCREAMING_SNAKE_CASE    (						self    :  List[Any]  ):
							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     _SCREAMING_SNAKE_CASE    (						self    :  Optional[Any]	,    snake_case__    :  Dict	,    snake_case__    :  Union[str, Any]	,    snake_case__    :  Union[str, Any]  ):
							lowerCAmelCase__   = {}
							result.update({"""sari""": compute_sari(sources=snake_case__	,    predictions=snake_case__	,    references=snake_case__  )}  )
							result.update({"""sacrebleu""": compute_sacrebleu(predictions=snake_case__	,    references=snake_case__  )}  )
							result.update({"""exact""": compute_em(predictions=snake_case__	,    references=snake_case__  )}  )
							return result




