





from collections import Counter

import sacrebleu
import sacremoses
from packaging import version

import datasets


__lowerCAmelCase 	=      '\\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'

__lowerCAmelCase 	=      '\\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'


__lowerCAmelCase 	=      '\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    (   _lowercase :  Any			,    _lowercase :  Union[str, Any]			,    _lowercase :  int			,    _lowercase :  Optional[int]							)  ->Any:
		UpperCamelCase__								=						[rgram for rgrams in rgramslist for rgram in rgrams]
		UpperCamelCase__								=						Counter(_lowercase							)

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

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

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

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

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

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

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

		return (keepscore, delscore_precision, addscore)

def      a    (   _lowercase :  List[str]			,    _lowercase :  str			,    _lowercase :  str							)  ->Dict:
		UpperCamelCase__								=						len(_lowercase							)

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

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

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

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

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

def      a    (   _lowercase :  Tuple			,    _lowercase :  bool = True			,    _lowercase :  str = "13a"			,    _lowercase :  bool = True							)  ->Union[str, Any]:
		# Normalization is requried for the ASSET dataset (one of the primary
		# datasets in sentence simplification) to allow using space
		# to split the sentence. Even though Wiki-Auto and TURK datasets,
		# do not require normalization, we do it for consistency.
		# Code adapted from the EASSE library [1] written by the authors of the ASSET dataset.
		# [1] https://github.com/feralvam/easse/blob/580bba7e1378fc8289c663f864e0487188fe8067/easse/utils/preprocessing.py#L7

		if lowercase:
				UpperCamelCase__								=						sentence.lower()

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

		if not return_str:
				UpperCamelCase__								=						normalized_sent.split()

		return normalized_sent




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




					def 						snake_case_		(    self							)    ->	List[str]:
							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 						snake_case_		(    self     ,   __lowerCAmelCase     ,   __lowerCAmelCase     ,   __lowerCAmelCase							)    ->	int:
							if not (len(_UpperCAmelCase							) == len(_UpperCAmelCase							) == len(_UpperCAmelCase							)):
									raise ValueError("""Sources length must match predictions and references lengths."""							)
							UpperCamelCase__								=						0
							for src, pred, refs in zip(_UpperCAmelCase     ,   _UpperCAmelCase     ,   _UpperCAmelCase							):
									sari_score += SARIsent(normalize(_UpperCAmelCase							)     ,   normalize(_UpperCAmelCase							)     ,   [normalize(_UpperCAmelCase							) for sent in refs]							)
							UpperCamelCase__								=						sari_score / len(_UpperCAmelCase							)
							return {"sari": 100 * sari_score}













import json
import os
import re
import unicodedata
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_UpperCAmelCase					:						Dict         =     logging.get_logger(__name__)

_UpperCAmelCase					:						int         =     {
    'src_vocab_file': 'vocab-src.json',
    'tgt_vocab_file': 'vocab-tgt.json',
    'merges_file': 'merges.txt',
}

_UpperCAmelCase					:						Optional[int]         =     {
    'src_vocab_file': {
        'stas/tiny-wmt19-en-de': 'https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/vocab-src.json'
    },
    'tgt_vocab_file': {
        'stas/tiny-wmt19-en-de': 'https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/vocab-tgt.json'
    },
    'merges_file': {'stas/tiny-wmt19-en-de': 'https://huggingface.co/stas/tiny-wmt19-en-de/resolve/main/merges.txt'},
}

_UpperCAmelCase					:						Optional[int]         =     {'stas/tiny-wmt19-en-de': 1024}
_UpperCAmelCase					:						List[Any]         =     {
    'stas/tiny-wmt19-en-de': {
        'langs': ['en', 'de'],
        'model_max_length': 1024,
        'special_tokens_map_file': None,
        'full_tokenizer_file': None,
    }
}






def  UpperCAmelCase__						(    lowerCamelCase	:			Dict    ):
   lowerCamelCase									=set()
   lowerCamelCase									=word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)    )
      lowerCamelCase									=char
   return pairs






def  UpperCAmelCase__						(    lowerCamelCase	:			Optional[Any]    ):
   lowerCamelCase									=text.replace("""，"""			,""","""    )
   lowerCamelCase									=re.sub(R"""。\s*"""			,""". """			,lowerCamelCase    )
   lowerCamelCase									=text.replace("""、"""			,""","""    )
   lowerCamelCase									=text.replace("""”"""			,"""\""""    )
   lowerCamelCase									=text.replace("""“"""			,"""\""""    )
   lowerCamelCase									=text.replace("""∶"""			,""":"""    )
   lowerCamelCase									=text.replace("""："""			,""":"""    )
   lowerCamelCase									=text.replace("""？"""			,"""?"""    )
   lowerCamelCase									=text.replace("""《"""			,"""\""""    )
   lowerCamelCase									=text.replace("""》"""			,"""\""""    )
   lowerCamelCase									=text.replace("""）"""			,""")"""    )
   lowerCamelCase									=text.replace("""！"""			,"""!"""    )
   lowerCamelCase									=text.replace("""（"""			,"""("""    )
   lowerCamelCase									=text.replace("""；"""			,""";"""    )
   lowerCamelCase									=text.replace("""１"""			,"""1"""    )
   lowerCamelCase									=text.replace("""」"""			,"""\""""    )
   lowerCamelCase									=text.replace("""「"""			,"""\""""    )
   lowerCamelCase									=text.replace("""０"""			,"""0"""    )
   lowerCamelCase									=text.replace("""３"""			,"""3"""    )
   lowerCamelCase									=text.replace("""２"""			,"""2"""    )
   lowerCamelCase									=text.replace("""５"""			,"""5"""    )
   lowerCamelCase									=text.replace("""６"""			,"""6"""    )
   lowerCamelCase									=text.replace("""９"""			,"""9"""    )
   lowerCamelCase									=text.replace("""７"""			,"""7"""    )
   lowerCamelCase									=text.replace("""８"""			,"""8"""    )
   lowerCamelCase									=text.replace("""４"""			,"""4"""    )
   lowerCamelCase									=re.sub(R"""．\s*"""			,""". """			,lowerCamelCase    )
   lowerCamelCase									=text.replace("""～"""			,"""~"""    )
   lowerCamelCase									=text.replace("""’"""			,"""'"""    )
   lowerCamelCase									=text.replace("""…"""			,"""..."""    )
   lowerCamelCase									=text.replace("""━"""			,"""-"""    )
   lowerCamelCase									=text.replace("""〈"""			,"""<"""    )
   lowerCamelCase									=text.replace("""〉"""			,""">"""    )
   lowerCamelCase									=text.replace("""【"""			,"""["""    )
   lowerCamelCase									=text.replace("""】"""			,"""]"""    )
   lowerCamelCase									=text.replace("""％"""			,"""%"""    )
   return text






def  UpperCAmelCase__						(    lowerCamelCase	:			Optional[int]    ):
   lowerCamelCase									=[]
   for char in text:
      lowerCamelCase									=unicodedata.category(lowerCamelCase    )
      if cat.startswith("""C"""    ):
         continue
      output.append(lowerCamelCase    )
   return "".join(lowerCamelCase    )







class 		lowerCAmelCase_				(  UpperCamelCase ):
     __lowerCamelCase       :    Optional[int] 	=     VOCAB_FILES_NAMES
     __lowerCamelCase       :    List[Any] 	=     PRETRAINED_VOCAB_FILES_MAP
     __lowerCamelCase       :    List[Any] 	=     PRETRAINED_INIT_CONFIGURATION
     __lowerCamelCase       :    Tuple 	=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __lowerCamelCase       :    Optional[int] 	=     ['''input_ids''', '''attention_mask''']





     def __init__(	self							, _UpperCAmelCase=None							, _UpperCAmelCase=None							, _UpperCAmelCase=None							, _UpperCAmelCase=None							, _UpperCAmelCase=False							, _UpperCAmelCase="<unk>"							, _UpperCAmelCase="<s>"							, _UpperCAmelCase="</s>"							, _UpperCAmelCase="<pad>"							, **_UpperCAmelCase							, )		->				Tuple:
        super().__init__(
            langs=_UpperCAmelCase							, src_vocab_file=_UpperCAmelCase							, tgt_vocab_file=_UpperCAmelCase							, merges_file=_UpperCAmelCase							, do_lower_case=_UpperCAmelCase							, unk_token=_UpperCAmelCase							, bos_token=_UpperCAmelCase							, sep_token=_UpperCAmelCase							, pad_token=_UpperCAmelCase							, **_UpperCAmelCase							, )

        try:
           import sacremoses
        except ImportError:
           raise ImportError(
               """You need to install sacremoses to use XLMTokenizer. """
               """See https://pypi.org/project/sacremoses/ for installation."""  )

        lowerCamelCase									=sacremoses

        lowerCamelCase									=src_vocab_file
        lowerCamelCase									=tgt_vocab_file
        lowerCamelCase									=merges_file
        lowerCamelCase									=do_lower_case

        # cache of sm.MosesPunctNormalizer instance
        lowerCamelCase									={}
        # cache of sm.MosesTokenizer instance
        lowerCamelCase									={}
        lowerCamelCase									={}

        if langs and len(_UpperCAmelCase  ) == 2:
           lowerCamelCase				,       lowerCamelCase									=langs
        else:
           raise ValueError(
               F'''arg `langs` needs to be a list of 2 langs, e.g. [\'en\', \'ru\'], but got {langs}. '''
               """Usually that means that tokenizer can't find a mapping for the given model path """
               """in PRETRAINED_VOCAB_FILES_MAP, and other maps of this tokenizer."""  )

        with open(_UpperCAmelCase							, encoding="""utf-8"""  ) as src_vocab_handle:
           lowerCamelCase									=json.load(_UpperCAmelCase  )
        with open(_UpperCAmelCase							, encoding="""utf-8"""  ) as tgt_vocab_handle:
           lowerCamelCase									=json.load(_UpperCAmelCase  )
           lowerCamelCase									={v: k for k, v in tgt_vocab.items()}
        with open(_UpperCAmelCase							, encoding="""utf-8"""  ) as merges_handle:
           lowerCamelCase									=merges_handle.read().split("""\n"""  )[:-1]
        lowerCamelCase									=[tuple(merge.split()[:2]  ) for merge in merges]
        lowerCamelCase									=dict(zip(_UpperCAmelCase							, range(len(_UpperCAmelCase  )  )  )  )
        lowerCamelCase									={}





     def 						lowerCamelCase							(	self  )		->				Dict[str, int]:
        return self.get_src_vocab()





     @property
     def 						lowerCamelCase							(	self  )		->				int:
        return self.src_vocab_size





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase  )		->				int:
        if lang not in self.cache_moses_punct_normalizer:
           lowerCamelCase									=self.sm.MosesPunctNormalizer(lang=_UpperCAmelCase  )
           lowerCamelCase									=punct_normalizer
        return self.cache_moses_punct_normalizer[lang].normalize(_UpperCAmelCase  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase  )		->				str:
        if lang not in self.cache_moses_tokenizer:
           lowerCamelCase									=self.sm.MosesTokenizer(lang=_UpperCAmelCase  )
           lowerCamelCase									=moses_tokenizer
        return self.cache_moses_tokenizer[lang].tokenize(
            _UpperCAmelCase							, aggressive_dash_splits=_UpperCAmelCase							, return_str=_UpperCAmelCase							, escape=_UpperCAmelCase  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase  )		->				Dict:
        if lang not in self.cache_moses_detokenizer:
           lowerCamelCase									=self.sm.MosesDetokenizer(lang=_UpperCAmelCase  )
           lowerCamelCase									=moses_detokenizer
        return self.cache_moses_detokenizer[lang].detokenize(_UpperCAmelCase  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase  )		->				List[str]:
        lowerCamelCase									=replace_unicode_punct(_UpperCAmelCase  )
        lowerCamelCase									=self.moses_punct_norm(_UpperCAmelCase							, _UpperCAmelCase  )
        lowerCamelCase									=remove_non_printing_char(_UpperCAmelCase  )
        return text





     @property
     def 						lowerCamelCase							(	self  )		->				Dict:
        return len(self.encoder  )





     @property
     def 						lowerCamelCase							(	self  )		->				Union[str, Any]:
        return len(self.decoder  )





     def 						lowerCamelCase							(	self  )		->				Optional[Any]:
        return dict(self.encoder							, **self.added_tokens_encoder  )





     def 						lowerCamelCase							(	self  )		->				Union[str, Any]:
        return dict(self.decoder							, **self.added_tokens_decoder  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase  )		->				Union[str, Any]:
        lowerCamelCase									=tuple(token[:-1]  ) + (token[-1] + """</w>""",)
        if token in self.cache:
           return self.cache[token]
        lowerCamelCase									=get_pairs(_UpperCAmelCase  )

        if not pairs:
           return token + "</w>"

        while True:
           lowerCamelCase									=min(_UpperCAmelCase							, key=lambda _UpperCAmelCase  : self.bpe_ranks.get(_UpperCAmelCase							, float("""inf"""  )  )  )
           if bigram not in self.bpe_ranks:
              break
           lowerCamelCase				,       lowerCamelCase									=bigram
           lowerCamelCase									=[]
           lowerCamelCase									=0
           while i < len(_UpperCAmelCase  ):
              try:
                 lowerCamelCase									=word.index(_UpperCAmelCase							, _UpperCAmelCase  )
              except ValueError:
                 new_word.extend(word[i:]  )
                 break
              else:
                 new_word.extend(word[i:j]  )
                 lowerCamelCase									=j

              if word[i] == first and i < len(_UpperCAmelCase  ) - 1 and word[i + 1] == second:
                 new_word.append(first + second  )
                 i += 2
              else:
                 new_word.append(word[i]  )
                 i += 1
           lowerCamelCase									=tuple(_UpperCAmelCase  )
           lowerCamelCase									=new_word
           if len(_UpperCAmelCase  ) == 1:
              break
           else:
              lowerCamelCase									=get_pairs(_UpperCAmelCase  )
        lowerCamelCase									=""" """.join(_UpperCAmelCase  )
        if word == "\n  </w>":
           lowerCamelCase									="""\n</w>"""
        lowerCamelCase									=word
        return word





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase="en"							, _UpperCAmelCase=False  )		->				str:
        lowerCamelCase									=self.src_lang

        if self.do_lower_case:
           lowerCamelCase									=text.lower()

        if bypass_tokenizer:
           lowerCamelCase									=text.split()
        else:
           lowerCamelCase									=self.moses_pipeline(_UpperCAmelCase							, lang=_UpperCAmelCase  )
           lowerCamelCase									=self.moses_tokenize(_UpperCAmelCase							, lang=_UpperCAmelCase  )

        lowerCamelCase									=[]
        for token in text:
           if token:
              split_tokens.extend(list(self.bpe(_UpperCAmelCase  ).split(""" """  )  )  )

        return split_tokens





     def 						lowerCamelCase							(	self							, _UpperCAmelCase  )		->				List[str]:
        return self.encoder.get(_UpperCAmelCase							, self.encoder.get(self.unk_token  )  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase  )		->				Tuple:
        return self.decoder.get(_UpperCAmelCase							, self.unk_token  )





     def 						lowerCamelCase							(	self							, _UpperCAmelCase  )		->				List[Any]:
        lowerCamelCase									=[t.replace(""" """							, """"""  ).replace("""</w>"""							, """ """  ) for t in tokens]
        lowerCamelCase									="""""".join(_UpperCAmelCase  ).split()
        # detokenize
        lowerCamelCase									=self.moses_detokenize(_UpperCAmelCase							, self.tgt_lang  )
        return text





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase = None  )		->				List[int]:
        lowerCamelCase									=[self.sep_token_id]

        # no bos used in fairseq
        if token_ids_a is None:
           return token_ids_a + sep
        return token_ids_a + sep + token_ids_a + sep





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase = None							, _UpperCAmelCase = False  )		->				List[int]:

        if already_has_special_tokens:
           return super().get_special_tokens_mask(
               token_ids_a=_UpperCAmelCase							, token_ids_a=_UpperCAmelCase							, already_has_special_tokens=_UpperCAmelCase  )
        # no bos used in fairseq
        if token_ids_a is not None:
           return ([0] * len(_UpperCAmelCase  )) + [1] + ([0] * len(_UpperCAmelCase  )) + [1]
        return ([0] * len(_UpperCAmelCase  )) + [1]





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase = None  )		->				List[int]:
        lowerCamelCase									=[self.sep_token_id]

        # no bos used in fairseq
        if token_ids_a is None:
           return len(token_ids_a + sep  ) * [0]
        return len(token_ids_a + sep  ) * [0] + len(token_ids_a + sep  ) * [1]





     def 						lowerCamelCase							(	self							, _UpperCAmelCase							, _UpperCAmelCase = None  )		->				Tuple[str]:
        if not os.path.isdir(_UpperCAmelCase  ):
           logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
           return

        lowerCamelCase									=os.path.join(
            _UpperCAmelCase							, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""src_vocab_file"""]  )
        lowerCamelCase									=os.path.join(
            _UpperCAmelCase							, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""tgt_vocab_file"""]  )
        lowerCamelCase									=os.path.join(
            _UpperCAmelCase							, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]  )

        with open(_UpperCAmelCase							, """w"""							, encoding="""utf-8"""  ) as f:
           f.write(json.dumps(self.encoder							, indent=2							, sort_keys=_UpperCAmelCase							, ensure_ascii=_UpperCAmelCase  ) + """\n"""  )

        with open(_UpperCAmelCase							, """w"""							, encoding="""utf-8"""  ) as f:
           lowerCamelCase									={v: k for k, v in self.decoder.items()}
           f.write(json.dumps(_UpperCAmelCase							, indent=2							, sort_keys=_UpperCAmelCase							, ensure_ascii=_UpperCAmelCase  ) + """\n"""  )

        lowerCamelCase									=0
        with open(_UpperCAmelCase							, """w"""							, encoding="""utf-8"""  ) as writer:
           for bpe_tokens, token_index in sorted(self.bpe_ranks.items()							, key=lambda _UpperCAmelCase  : kv[1]  ):
              if index != token_index:
                 logger.warning(
                     F'''Saving vocabulary to {merges_file}: BPE merge indices are not consecutive.'''
                     """ Please check that the tokenizer is not corrupted!"""  )
                 lowerCamelCase									=token_index
              writer.write(""" """.join(_UpperCAmelCase  ) + """\n"""  )
              index += 1

        return src_vocab_file, tgt_vocab_file, merges_file





     def __getstate__(	self  )		->				List[Any]:
        lowerCamelCase									=self.__dict__.copy()
        lowerCamelCase									=None
        return state





     def __setstate__(	self							, _UpperCAmelCase  )		->				Union[str, Any]:
        lowerCamelCase									=d

        try:
           import sacremoses
        except ImportError:
           raise ImportError(
               """You need to install sacremoses to use XLMTokenizer. """
               """See https://pypi.org/project/sacremoses/ for installation."""  )

        lowerCamelCase									=sacremoses