

from collections import Counter

import sacrebleu
import sacremoses
from packaging import version

import datasets


lowercase_     =       '\\n@inproceedings{xu-etal-2016-optimizing,\ntitle = {Optimizing Statistical Machine Translation for Text Simplification},\nauthors={Xu, Wei and Napoles, Courtney and Pavlick, Ellie and Chen, Quanze and Callison-Burch, Chris},\njournal = {Transactions of the Association for Computational Linguistics},\nvolume = {4},\nyear={2016},\nurl = {https://www.aclweb.org/anthology/Q16-1029},\npages = {401--415},\n}\n'

lowercase_     =       '\\nSARI is a metric used for evaluating automatic text simplification systems.\nThe metric compares the predicted simplified sentences against the reference\nand the source sentences. It explicitly measures the goodness of words that are\nadded, deleted and kept by the system.\nSari = (F1_add + F1_keep + P_del) / 3\nwhere\nF1_add: n-gram F1 score for add operation\nF1_keep: n-gram F1 score for keep operation\nP_del: n-gram precision score for delete operation\nn = 4, as in the original paper.\n\nThis implementation is adapted from Tensorflow\'s tensor2tensor implementation [3].\nIt has two differences with the original GitHub [1] implementation:\n  (1) Defines 0/0=1 instead of 0 to give higher scores for predictions that match\n      a target exactly.\n  (2) Fixes an alleged bug [2] in the keep score computation.\n[1] https://github.com/cocoxu/simplification/blob/master/SARI.py\n    (commit 0210f15)\n[2] https://github.com/cocoxu/simplification/issues/6\n[3] https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/utils/sari_hook.py\n'


lowercase_     =       '\nCalculates sari score (between 0 and 100) given a list of source and predicted\nsentences, and a list of lists of reference sentences.\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\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 .","About 95 species are now accepted .","95 species are now accepted ."]]\n    >>> sari = datasets.load_metric("sari")\n    >>> results = sari.compute(sources=sources, predictions=predictions, references=references)\n    >>> print(results)\n    {\'sari\': 26.953601953601954}\n'
def 					a				(      A__     :       List[Any]				,       A__     :       Tuple				,       A__     :       Any				,       A__     :       List[Any]					)   ->				Union[str, Any]:





      """simple docstring"""



      _lowercase     	=[rgram for rgrams in rgramslist for rgram in rgrams]
      _lowercase     	=Counter(A__					)

      _lowercase     	=Counter(A__					)
      _lowercase     	=Counter()
      for sgram, scount in sgramcounter.items():
            _lowercase     	=scount * numref

      _lowercase     	=Counter(A__					)
      _lowercase     	=Counter()
      for cgram, ccount in cgramcounter.items():
            _lowercase     	=ccount * numref

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

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

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

      # ADDITION
      _lowercase     	=set(A__					) - set(A__					)
      _lowercase     	=set(A__					) & set(A__					)
      _lowercase     	=set(A__					) - set(A__					)

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

      return (keepscore, delscore_precision, addscore)
def 					a				(      A__     :       Optional[Any]				,       A__     :       Optional[Any]				,       A__     :       Union[str, Any]					)   ->				Union[str, Any]:





      """simple docstring"""



      _lowercase     	=len(A__					)

      _lowercase     	=ssent.split(' '					)
      _lowercase     	=csent.split(' '					)
      _lowercase     	=[]
      _lowercase     	=[]
      _lowercase     	=[]
      _lowercase     	=[]
      _lowercase     	=[]
      _lowercase     	=[]

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

      for i in range(0				,       len(A__					) - 1					):
            if i < len(A__					) - 1:
                  _lowercase     	=sagrams[i] + ' ' + sagrams[i + 1]
                  sagrams.append(A__					)
            if i < len(A__					) - 2:
                  _lowercase     	=sagrams[i] + ' ' + sagrams[i + 1] + ' ' + sagrams[i + 2]
                  sagrams.append(A__					)
            if i < len(A__					) - 3:
                  _lowercase     	=sagrams[i] + ' ' + sagrams[i + 1] + ' ' + sagrams[i + 2] + ' ' + sagrams[i + 3]
                  sagrams.append(A__					)

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

      ((_lowercase)	,	(_lowercase)	,	(_lowercase))     	=SARIngram(A__				,       A__				,       A__				,       A__					)
      ((_lowercase)	,	(_lowercase)	,	(_lowercase))     	=SARIngram(A__				,       A__				,       A__				,       A__					)
      ((_lowercase)	,	(_lowercase)	,	(_lowercase))     	=SARIngram(A__				,       A__				,       A__				,       A__					)
      ((_lowercase)	,	(_lowercase)	,	(_lowercase))     	=SARIngram(A__				,       A__				,       A__				,       A__					)
      _lowercase     	=sum([keepascore, keepascore, keepascore, keepascore]					) / 4
      _lowercase     	=sum([delascore, delascore, delascore, delascore]					) / 4
      _lowercase     	=sum([addascore, addascore, addascore, addascore]					) / 4
      _lowercase     	=(avgkeepscore + avgdelscore + avgaddscore) / 3
      return finalscore
def 					a				(      A__     :       Optional[int]				,       A__     :       bool = True				,       A__     :       str = "13a"				,       A__     :       bool = True					)   ->				List[str]:





      """simple docstring"""



      if lowercase:
            _lowercase     	=sentence.lower()

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

      if not return_str:
            _lowercase     	=normalized_sent.split()

      return normalized_sent







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




  def   A__					(    self )  ->			List[Any]:
        '''simple docstring'''






        return datasets.MetricInfo(
            description=_DESCRIPTION							,       citation=_CITATION							,       inputs_description=_KWARGS_DESCRIPTION							,       features=datasets.Features(
                {
                    'sources': datasets.Value('string'							,       id='sequence' ),
                    'predictions': datasets.Value('string'							,       id='sequence' ),
                    'references': datasets.Sequence(datasets.Value('string'							,       id='sequence' )							,       id='references' ),
                } )							,       codebase_urls=[
                'https://github.com/cocoxu/simplification/blob/master/SARI.py',
                'https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/utils/sari_hook.py',
            ]							,       reference_urls=['https://www.aclweb.org/anthology/Q16-1029.pdf']							,       )




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )  ->			Optional[int]:
        '''simple docstring'''






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





#
# Sort large text files in a minimum amount of memory
#
import argparse
import os





class 			__lowerCAmelCase					:
  _a						      =  """block_{0}.dat"""




  def __init__(    self							,       lowerCAmelCase )  ->			List[str]:
        '''simple docstring'''






        _lowercase     	=filename
        _lowercase     	=[]




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase )  ->			str:
        '''simple docstring'''






        _lowercase     	=self.BLOCK_FILENAME_FORMAT.format(lowerCAmelCase )
        with open(lowerCAmelCase							,       'w' ) as file:
              file.write(lowerCAmelCase )
        self.block_filenames.append(lowerCAmelCase )




  def   A__					(    self )  ->			Dict:
        '''simple docstring'''






        return self.block_filenames




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase=None )  ->			Dict:
        '''simple docstring'''






        _lowercase     	=0
        with open(self.filename ) as file:
              while True:
                    _lowercase     	=file.readlines(lowerCAmelCase )

                    if lines == []:
                          break

                    if sort_key is None:
                          lines.sort()
                    else:
                          lines.sort(key=lowerCAmelCase )

                    self.write_block(''.join(lowerCAmelCase )							,       lowerCAmelCase )
                    i += 1




  def   A__					(    self )  ->			Optional[Any]:
        '''simple docstring'''






        map(os.remove							,       self.block_filenames )





class 			__lowerCAmelCase					:




  def   A__					(    self							,       lowerCAmelCase )  ->			Union[str, Any]:
        '''simple docstring'''






        _lowercase     	=-1
        _lowercase     	=None

        for i in range(len(lowerCAmelCase ) ):
              if min_str is None or choices[i] < min_str:
                    _lowercase     	=i

        return min_index





class 			__lowerCAmelCase					:




  def __init__(    self							,       lowerCAmelCase )  ->			int:
        '''simple docstring'''






        _lowercase     	=files
        _lowercase     	=set()
        _lowercase     	=len(lowerCAmelCase )
        _lowercase     	={i: None for i in range(self.num_buffers )}




  def   A__					(    self )  ->			int:
        '''simple docstring'''






        return {
            i: self.buffers[i] for i in range(self.num_buffers ) if i not in self.empty
        }




  def   A__					(    self )  ->			Union[str, Any]:
        '''simple docstring'''






        for i in range(self.num_buffers ):
              if self.buffers[i] is None and i not in self.empty:
                    _lowercase     	=self.files[i].readline()

                    if self.buffers[i] == "":
                          self.empty.add(lowerCAmelCase )
                          self.files[i].close()

        if len(self.empty ) == self.num_buffers:
              return False

        return True




  def   A__					(    self							,       lowerCAmelCase )  ->			Optional[int]:
        '''simple docstring'''






        _lowercase     	=self.buffers[index]
        _lowercase     	=None

        return value





class 			__lowerCAmelCase					:




  def __init__(    self							,       lowerCAmelCase )  ->			Any:
        '''simple docstring'''






        _lowercase     	=merge_strategy




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )  ->			str:
        '''simple docstring'''






        _lowercase     	=FilesArray(self.get_file_handles(lowerCAmelCase							,       lowerCAmelCase ) )
        with open(lowerCAmelCase							,       'w'							,       lowerCAmelCase ) as outfile:
              while buffers.refresh():
                    _lowercase     	=self.merge_strategy.select(buffers.get_dict() )
                    outfile.write(buffers.unshift(lowerCAmelCase ) )




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase )  ->			Optional[int]:
        '''simple docstring'''






        _lowercase     	={}

        for i in range(len(lowerCAmelCase ) ):
              _lowercase     	=open(filenames[i]							,       'r'							,       lowerCAmelCase )  # noqa: UP015

        return files





class 			__lowerCAmelCase					:




  def __init__(    self							,       lowerCAmelCase )  ->			Union[str, Any]:
        '''simple docstring'''






        _lowercase     	=block_size




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase=None )  ->			Dict:
        '''simple docstring'''






        _lowercase     	=self.get_number_blocks(lowerCAmelCase							,       self.block_size )
        _lowercase     	=FileSplitter(lowerCAmelCase )
        splitter.split(self.block_size							,       lowerCAmelCase )

        _lowercase     	=FileMerger(NWayMerge() )
        _lowercase     	=self.block_size / (num_blocks + 1)
        merger.merge(splitter.get_block_filenames()							,       filename + '.out'							,       lowerCAmelCase )

        splitter.cleanup()




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase )  ->			Tuple:
        '''simple docstring'''






        return (os.stat(lowerCAmelCase ).st_size / block_size) + 1
def 					a				(      A__     :       Tuple					)   ->				Optional[Any]:





      """simple docstring"""



      if string[-1].lower() == "k":
            return int(string[:-1]					) * 1024
      elif string[-1].lower() == "m":
            return int(string[:-1]					) * 1024 * 1024
      elif string[-1].lower() == "g":
            return int(string[:-1]					) * 1024 * 1024 * 1024
      else:
            return int(A__					)
def 					a				(      )   ->				str:





      """simple docstring"""



      _lowercase     	=argparse.ArgumentParser()
      parser.add_argument(
          '-m'				,       '--mem'				,       help='amount of memory to use for sorting'				,       default='100M'					)
      parser.add_argument(
          'filename'				,       metavar='<filename>'				,       nargs=1				,       help='name of file to sort'					)
      _lowercase     	=parser.parse_args()

      _lowercase     	=ExternalSort(parse_memory(args.mem					)					)
      sorter.sort(args.filename[0]					)


if __name__ == "__main__":
  main()


