
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
					from transformers.pipelines.conversational import Conversation

SCREAMING_SNAKE_CASE				:Union[str, Any]									=							logging.get_logger(__name__)


SCREAMING_SNAKE_CASE				:Tuple									=							{
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

SCREAMING_SNAKE_CASE				:Dict									=							{
    'vocab_file': {'facebook/blenderbot-3B': 'https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json'},
    'merges_file': {'facebook/blenderbot-3B': 'https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt'},
    'tokenizer_config_file': {
        'facebook/blenderbot-3B': 'https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json'
    },
}

SCREAMING_SNAKE_CASE				:Union[str, Any]									=							{'facebook/blenderbot-3B': 128}


@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 		UpperCAmelCase     (      )						->      Tuple:







				"""simple docstring"""



				__A       =					(
				    list(range(ord("!"		)						,  ord("~"		) + 1		)		) + list(range(ord("¡"		)						,  ord("¬"		) + 1		)		) + list(range(ord("®"		)						,  ord("ÿ"		) + 1		)		)
				)
				__A       =					bs[:]
				__A       =					0
				for b in range(2**8		):
								if b not in bs:
												bs.append(__UpperCAmelCase		)
												cs.append(2**8 + n		)
												n += 1
				__A       =					[chr(__UpperCAmelCase		) for n in cs]
				return dict(zip(__UpperCAmelCase						,  __UpperCAmelCase		)		)


def 		UpperCAmelCase     (      a_		)						->      Tuple:







				"""simple docstring"""



				__A       =					set()
				__A       =					word[0]
				for char in word[1:]:
								pairs.add((prev_char, char)		)
								__A       =					char
				return pairs





class 				UpperCAmelCase (    _snake_case    ):




	'''simple docstring'''





	snake_case_          =	VOCAB_FILES_NAMES
	snake_case_          =	PRETRAINED_VOCAB_FILES_MAP
	snake_case_          =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	snake_case_          =	['input_ids', 'attention_mask']






	def __init__(			self   :					Dict				,A   :					Tuple				,A   :					List[Any]				,A   :					Optional[int]="replace"				,A   :					Tuple="<s>"				,A   :					Optional[Any]="</s>"				,A   :					Optional[Any]="</s>"				,A   :					Union[str, Any]="<s>"				,A   :					Optional[Any]="<unk>"				,A   :					Any="<pad>"				,A   :					List[str]="<mask>"				,A   :					Optional[Any]=False				,**A   :					int				,):
					__A       =					AddedToken(A				,lstrip=A				,rstrip=A					) if isinstance(A				,A					) else bos_token
					__A       =					AddedToken(A				,lstrip=A				,rstrip=A					) if isinstance(A				,A					) else eos_token
					__A       =					AddedToken(A				,lstrip=A				,rstrip=A					) if isinstance(A				,A					) else sep_token
					__A       =					AddedToken(A				,lstrip=A				,rstrip=A					) if isinstance(A				,A					) else cls_token
					__A       =					AddedToken(A				,lstrip=A				,rstrip=A					) if isinstance(A				,A					) else unk_token
					__A       =					AddedToken(A				,lstrip=A				,rstrip=A					) if isinstance(A				,A					) else pad_token

					# Mask token behave like a normal word, i.e. include the space before it
					__A       =					AddedToken(A				,lstrip=A				,rstrip=A					) if isinstance(A				,A					) else mask_token

					super().__init__(
					    errors=A				,bos_token=A				,eos_token=A				,unk_token=A				,sep_token=A				,cls_token=A				,pad_token=A				,mask_token=A				,add_prefix_space=A				,**A				,)

					with open(A				,encoding="utf-8"					) as vocab_handle:
									__A       =					json.load(A					)
					__A       =					{v: k for k, v in self.encoder.items()}
					__A       =					errors  # how to handle errors in decoding
					__A       =					bytes_to_unicode()
					__A       =					{v: k for k, v in self.byte_encoder.items()}
					with open(A				,encoding="utf-8"					) as merges_handle:
									__A       =					merges_handle.read().split("\n"					)[1:-1]
					__A       =					[tuple(merge.split()					) for merge in bpe_merges]
					__A       =					dict(zip(A				,range(len(A					)					)					)					)
					__A       =					{}
					__A       =					add_prefix_space

					# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
					__A       =					re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"					)






	@property
	# Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
	def 							UpperCamelCase_    (			self   :					List[Any]					):
					return len(self.encoder					)






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






	def 							UpperCamelCase_    (			self   :					Dict				,A   :					Dict					):

					if token in self.cache:
									return self.cache[token]
					__A       =					tuple(A					)
					__A       =					get_pairs(A					)

					if not pairs:
									return token

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

													if word[i] == first and i < len(A					) - 1 and word[i + 1] == second:
																	new_word.append(first + second					)
																	i += 2
													else:
																	new_word.append(word[i]					)
																	i += 1
									__A       =					tuple(A					)
									__A       =					new_word
									if len(A					) == 1:
													break
									else:
													__A       =					get_pairs(A					)
					__A       =					" ".join(A					)
					__A       =					word
					return word






	def 							UpperCamelCase_    (			self   :					List[str]				,A   :					Any					):
					__A       =					[]
					for token in re.findall(self.pat				,A					):
									__A       =					"".join(
									    self.byte_encoder[b] for b in token.encode("utf-8"					)					)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
									bpe_tokens.extend(bpe_token for bpe_token in self.bpe(A					).split(" "					)					)
					return bpe_tokens






	def 							UpperCamelCase_    (			self   :					Any				,A   :					Union[str, Any]					):
					return self.encoder.get(A				,self.encoder.get(self.unk_token					)					)






	def 							UpperCamelCase_    (			self   :					Dict				,A   :					List[Any]					):
					return self.decoder.get(A					)






	def 							UpperCamelCase_    (			self   :					Optional[int]				,A   :					Any					):
					__A       =					"".join(A					)
					__A       =					bytearray([self.byte_decoder[c] for c in text]					).decode("utf-8"				,errors=self.errors					)
					return text






	def 							UpperCamelCase_    (			self   :					Any				,A   :					str				,A   :					Optional[str] = None					):

					if not os.path.isdir(A					):
									logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''					)
									return
					__A       =					os.path.join(
					    A				,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)
					__A       =					os.path.join(
					    A				,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]					)

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

					__A       =					0
					with open(A				,"w"				,encoding="utf-8"					) as writer:
									writer.write("#version: 0.2\n"					)
									for bpe_tokens, token_index in sorted(self.bpe_ranks.items()				,key=lambda A					: kv[1]					):
													if index != token_index:
																	logger.warning(
																	    f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
																	    " Please check that the tokenizer is not corrupted!"					)
																	__A       =					token_index
													writer.write(" ".join(A					) + "\n"					)
													index += 1

					return vocab_file, merge_file






	def 							UpperCamelCase_    (			self   :					List[str]				,A   :					List[int]				,A   :					Optional[List[int]] = None				,A   :					bool = False					):

					if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=A				,token_ids_a=A				,already_has_special_tokens=A					)

					if token_ids_a is None:
									return [1] + ([0] * len(A					)) + [1]
					return [1] + ([0] * len(A					)) + [1, 1] + ([0] * len(A					)) + [1]






	def 							UpperCamelCase_    (			self   :					Optional[Any]				,A   :					List[int]				,A   :					Optional[List[int]] = None					):
					__A       =					[self.sep_token_id]
					__A       =					[self.cls_token_id]

					if token_ids_a is None:
									return len(cls + token_ids_a + sep					) * [0]
					return len(cls + token_ids_a + sep + sep + token_ids_a + sep					) * [0]






	def 							UpperCamelCase_    (			self   :					Any				,A   :					List[str]				,A   :					List[str]=False				,**A   :					List[Any]					):
					__A       =					kwargs.pop("add_prefix_space"				,self.add_prefix_space					)
					if (is_split_into_words or add_prefix_space) and (len(A					) > 0 and not text[0].isspace()):
									__A       =					" " + text
					return (text, kwargs)






	def 							UpperCamelCase_    (			self   :					Any				,A   :					List[int]				,A   :					Optional[List[int]] = None					):
					return token_ids_a + [self.eos_token_id]







	def 							UpperCamelCase_    (			self   :					List[Any]				,A   :					"Conversation"					):
					__A       =					[]
					for is_user, text in conversation.iter_texts():
									if is_user:
													# We need to space prefix as it's being done within blenderbot
													inputs.append(" " + text					)
									else:
													# Generated responses should contain them already.
													inputs.append(A					)

					__A       =					"  ".join(A					)
					__A       =					self.encode(A					)
					if len(A					) > self.model_max_length:
									__A       =					input_ids[-self.model_max_length :]
									logger.warning(f'''Trimmed input from conversation as it was longer than {self.model_max_length} tokens.'''					)
					return input_ids







'''simple docstring'''

import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple

import numpy as np

from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
    from transformers.pipelines.conversational import Conversation


a   	=    logging.get_logger(__name__)

a   	=    {"vocab_file": "vocab.txt", "emoji_file": "emoji.json"}

a   	=    {
    "vocab_file": {
        "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/vocab.txt",
    },
    "emoji_file": {
        "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/emoji.json",
    },
}

a   	=    {
    "abeja/gpt-neox-japanese-2.7b": 2048,
}

def     __magic_name__							(				__UpperCAmelCase				,						__UpperCAmelCase   )    ->       Any:

   '''simple docstring'''







   with open(__UpperCAmelCase				,						"""r"""				,						encoding="""utf-8"""   ) as f:
      __SCREAMING_SNAKE_CASE   				=							json.loads(f.read()   )

   __SCREAMING_SNAKE_CASE   				=							collections.OrderedDict()
   __SCREAMING_SNAKE_CASE   				=							collections.OrderedDict()
   __SCREAMING_SNAKE_CASE   				=							collections.OrderedDict()
   with open(__UpperCAmelCase				,						"""r"""				,						encoding="""utf-8"""   ) as f:
      __SCREAMING_SNAKE_CASE   				=							f.readlines()
   __SCREAMING_SNAKE_CASE   				=							[[t.rstrip("""\n"""   )] if (t == """,""" or """,""" not in t) else t.rstrip("""\n"""   ).split(""","""   ) for t in token]
   for idx, b in enumerate(__UpperCAmelCase   ):
      __SCREAMING_SNAKE_CASE   				=							b
      __SCREAMING_SNAKE_CASE   				=							idx
      for wd in b:
         __SCREAMING_SNAKE_CASE   				=							idx

   return vocab, raw_vocab, ids_to_tokens, emoji







class __a			( _snake_case      ):
   __UpperCamelCase :			Tuple						   =						VOCAB_FILES_NAMES
   __UpperCamelCase :			Tuple						   =						PRETRAINED_VOCAB_FILES_MAP
   __UpperCamelCase :			Any						   =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCamelCase :			Union[str, Any]						   =						['input_ids', 'attention_mask']





   def __init__(       self					:      Dict					,lowerCamelCase					:      Union[str, Any]					,lowerCamelCase					:      int					,lowerCamelCase					:      str="<|endoftext|>"					,lowerCamelCase					:      List[Any]="<|endoftext|>"					,lowerCamelCase					:      str="<|startoftext|>"					,lowerCamelCase					:      Dict="<|endoftext|>"					,lowerCamelCase					:      int=False					,**lowerCamelCase					:      str					,):

      '''simple docstring'''

      super().__init__(
          unk_token=lowerCamelCase					,pad_token=lowerCamelCase					,bos_token=lowerCamelCase					,eos_token=lowerCamelCase					,do_clean_text=lowerCamelCase					,**lowerCamelCase					,)
      if not os.path.isfile(lowerCamelCase     ):
         raise ValueError(
             f"""Can't find a vocabulary file at path '{vocab_file}'. To load the vocabulary from a Google pretrained"""
             """ model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`"""     )
      if not os.path.isfile(lowerCamelCase     ):
         raise ValueError(
             f"""Can't find a emoji file at path '{emoji_file}'. To load the emoji information from a Google"""
             """ pretrained model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`"""     )
      __SCREAMING_SNAKE_CASE   				=							do_clean_text
      __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE   				=							load_vocab_and_emoji(lowerCamelCase					,lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							SubWordJapaneseTokenizer(
          vocab=self.vocab					,ids_to_tokens=self.ids_to_tokens					,emoji=self.emoji     )





   @property
   def   UpperCAmelCase__  (       self					:      Optional[Any]     ):

      '''simple docstring'''

      return len(self.raw_vocab     )





   def   UpperCAmelCase__  (       self					:      List[str]     ):

      '''simple docstring'''

      return dict(self.raw_vocab					,**self.added_tokens_encoder     )





   def   UpperCAmelCase__  (       self					:      Dict					,lowerCamelCase					:      str     ):

      '''simple docstring'''

      return self.subword_tokenizer.tokenize(lowerCamelCase					,clean=self.do_clean_text     )





   def   UpperCAmelCase__  (       self					:      Union[str, Any]					,lowerCamelCase					:      Union[str, Any]     ):

      '''simple docstring'''

      return self.vocab.get(lowerCamelCase					,self.vocab.get(self.unk_token     )     )





   def   UpperCAmelCase__  (       self					:      List[Any]					,lowerCamelCase					:      Optional[Any]     ):

      '''simple docstring'''

      return self.subword_tokenizer.convert_id_to_token(lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      List[str]					,lowerCamelCase					:      str     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							"""""".join(lowerCamelCase     ).strip()
      return out_string





   def   UpperCAmelCase__  (       self					:      List[str]					,lowerCamelCase					:      "Conversation"     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							[]
      for is_user, text in conversation.iter_texts():
         input_ids.extend(self.encode(lowerCamelCase					,add_special_tokens=lowerCamelCase     ) + [self.eos_token_id]     )

      if len(lowerCamelCase     ) > self.model_max_length:
         __SCREAMING_SNAKE_CASE   				=							input_ids[-self.model_max_length :]
      return input_ids





   def   UpperCAmelCase__  (       self					:      Dict					,lowerCamelCase					:      str					,lowerCamelCase					:      Optional[str] = None     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							0
      if os.path.isdir(lowerCamelCase     ):
         __SCREAMING_SNAKE_CASE   				=							os.path.join(
             lowerCamelCase					,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]     )
         __SCREAMING_SNAKE_CASE   				=							os.path.join(
             lowerCamelCase					,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""emoji_file"""]     )
      else:
         __SCREAMING_SNAKE_CASE   				=							(
             (filename_prefix + """-""" if filename_prefix else """""") + save_directory + VOCAB_FILES_NAMES["""vocab_file"""]
         )
         __SCREAMING_SNAKE_CASE   				=							(
             (filename_prefix + """-""" if filename_prefix else """""") + save_directory + VOCAB_FILES_NAMES["""emoji_file"""]
         )
      with open(lowerCamelCase					,"""w"""					,encoding="""utf-8"""     ) as writer:
         for token_index, token in self.ids_to_tokens.items():
            if index != token_index:
               logger.warning(
                   f"""Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."""
                   """ Please check that the vocabulary is not corrupted!"""     )
               __SCREAMING_SNAKE_CASE   				=							token_index
            writer.write(""",""".join(lowerCamelCase     ) + """\n"""     )
            index += 1
      with open(lowerCamelCase					,"""w"""					,encoding="""utf-8"""     ) as writer:
         json.dump(self.emoji					,lowerCamelCase     )
      return vocab_file, emoji_file







class __a			( _snake_case      ):





   def __init__(       self					:      Tuple					,lowerCamelCase					:      List[str]					,lowerCamelCase					:      Union[str, Any]					,lowerCamelCase					:      Optional[int]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							vocab  # same as swe
      __SCREAMING_SNAKE_CASE   				=							ids_to_tokens  # same as bpe
      __SCREAMING_SNAKE_CASE   				=							emoji
      __SCREAMING_SNAKE_CASE   				=							np.max([len(lowerCamelCase     ) for w in self.vocab.keys()]     )
      __SCREAMING_SNAKE_CASE   				=							re.compile(r"""(https?|ftp)(:\/\/[-_\.!~*\'()a-zA-Z0-9;\/?:\@&=\+$,%#]+)"""     )
      __SCREAMING_SNAKE_CASE   				=							re.compile(r"""[A-Za-z0-9\._+]*@[\-_0-9A-Za-z]+(\.[A-Za-z]+)*"""     )
      __SCREAMING_SNAKE_CASE   				=							re.compile(r"""[\(]{0,1}[0-9]{2,4}[\)\-\(]{0,1}[0-9]{2,4}[\)\-]{0,1}[0-9]{3,4}"""     )
      __SCREAMING_SNAKE_CASE   				=							re.compile(
          r"""([12]\d{3}[/\-年])*(0?[1-9]|1[0-2])[/\-月]((0?[1-9]|[12][0-9]|3[01])日?)*(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*"""     )
      __SCREAMING_SNAKE_CASE   				=							re.compile(
          r"""(明治|大正|昭和|平成|令和|㍾|㍽|㍼|㍻|\u32ff)\d{1,2}年(0?[1-9]|1[0-2])月(0?[1-9]|[12][0-9]|3[01])日(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*"""     )
      __SCREAMING_SNAKE_CASE   				=							re.compile(
          r"""((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*億)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*万)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*千)*(0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*(千円|万円|千万円|円|千ドル|万ドル|千万ドル|ドル|千ユーロ|万ユーロ|千万ユーロ|ユーロ)+(\(税込\)|\(税抜\)|\+tax)*"""     )
      __SCREAMING_SNAKE_CASE   				=							"""─━│┃┄┅┆┇┈┉┊┋┌┍┎┏┐┑┒┓└┕┖┗┘┙┚┛├┝┞┟┠┡┢┣┤┥┦┧┨┩┪┫┬┭┮┯┰┱┲┳┴┵┶┷┸┹┺┻┼┽┾┿╀╁╂╃╄╅╆╇╈╉╊╋╌╍╎╏═║╒╓╔╕╖╗╘╙╚╛╜╝╞╟╠╡╢╣╤╥╦╧╨╩╪╫╬╭╮╯╰╱╲╳╴╵╶╷╸╹╺╻╼╽╾╿"""
      __SCREAMING_SNAKE_CASE   				=							"""▀▁▂▃▄▅▆▇█▉▊▋▌▍▎▏▐░▒▓▔▕▖▗▘▙▚▛▜▝▞▟"""
      __SCREAMING_SNAKE_CASE   				=							str.maketrans({k: """<BLOCK>""" for k in keisen + blocks}     )





   def __len__(       self					:      List[str]     ):

      '''simple docstring'''

      return len(self.ids_to_tokens     )





   def   UpperCAmelCase__  (       self					:      Optional[int]					,lowerCamelCase					:      Dict     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							self.content_repattera.sub("""<URL>"""					,lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							self.content_repattera.sub("""<EMAIL>"""					,lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							self.content_repattera.sub("""<TEL>"""					,lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							self.content_repattera.sub("""<DATE>"""					,lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							self.content_repattera.sub("""<DATE>"""					,lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							self.content_repattera.sub("""<PRICE>"""					,lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							content.translate(self.content_transa     )
      while "<BLOCK><BLOCK>" in content:
         __SCREAMING_SNAKE_CASE   				=							content.replace("""<BLOCK><BLOCK>"""					,"""<BLOCK>"""     )
      return content





   def   UpperCAmelCase__  (       self					:      Dict					,lowerCamelCase					:      Optional[Any]					,lowerCamelCase					:      List[str]=False     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							text.replace(""" """					,"""<SP>"""     )
      __SCREAMING_SNAKE_CASE   				=							text.replace("""　"""					,"""<SP>"""     )
      __SCREAMING_SNAKE_CASE   				=							text.replace("""\r\n"""					,"""<BR>"""     )
      __SCREAMING_SNAKE_CASE   				=							text.replace("""\n"""					,"""<BR>"""     )
      __SCREAMING_SNAKE_CASE   				=							text.replace("""\r"""					,"""<BR>"""     )
      __SCREAMING_SNAKE_CASE   				=							text.replace("""\t"""					,"""<TAB>"""     )
      __SCREAMING_SNAKE_CASE   				=							text.replace("""—"""					,"""ー"""     )
      __SCREAMING_SNAKE_CASE   				=							text.replace("""−"""					,"""ー"""     )
      for k, v in self.emoji["emoji"].items():
         if k in text:
            __SCREAMING_SNAKE_CASE   				=							text.replace(lowerCamelCase					,lowerCamelCase     )
      if clean:
         __SCREAMING_SNAKE_CASE   				=							self.clean_text(lowerCamelCase     )

      def check_simbol(lowerCamelCase					:      List[str]     ):
         __SCREAMING_SNAKE_CASE   				=							x.encode()
         if len(lowerCamelCase     ) == 1 and len(lowerCamelCase     ) == 2:
            __SCREAMING_SNAKE_CASE   				=							(int(e[0]     ) << 8) + int(e[1]     )
            if (
                (c >= 0xC_2A1 and c <= 0xC_2BF)
                or (c >= 0xC_780 and c <= 0xC_783)
                or (c >= 0xC_AB9 and c <= 0xC_BBF)
                or (c >= 0xC_C80 and c <= 0xC_DA2)
            ):
               return True
         return False

      def checkuae(lowerCamelCase					:      Union[str, Any]     ):
         __SCREAMING_SNAKE_CASE   				=							x.encode()
         if len(lowerCamelCase     ) == 1 and len(lowerCamelCase     ) == 3:
            __SCREAMING_SNAKE_CASE   				=							(int(e[0]     ) << 16) + (int(e[1]     ) << 8) + int(e[2]     )
            if c >= 0xE28_080 and c <= 0xE2B_07F:
               return True
         return False

      __SCREAMING_SNAKE_CASE   				=							0
      __SCREAMING_SNAKE_CASE   				=							[]
      while pos < len(lowerCamelCase     ):
         __SCREAMING_SNAKE_CASE   				=							min(len(lowerCamelCase     )					,pos + self.maxlen + 1     ) if text[pos] == """<""" else pos + 3
         __SCREAMING_SNAKE_CASE   				=							[]  # (token_id, token, pos)
         for e in range(lowerCamelCase					,lowerCamelCase					,-1     ):
            __SCREAMING_SNAKE_CASE   				=							text[pos:e]
            if wd in self.vocab:
               if wd[0] == "<" and len(lowerCamelCase     ) > 2:
                  __SCREAMING_SNAKE_CASE   				=							[(self.vocab[wd], wd, e)]
                  break
               else:
                  candidates.append((self.vocab[wd], wd, e)     )
         if len(lowerCamelCase     ) > 0:
            # the smallest token_id is adopted
            __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE   				=							sorted(lowerCamelCase					,key=lambda lowerCamelCase     : x[0]     )[0]
            result.append(lowerCamelCase     )
            __SCREAMING_SNAKE_CASE   				=							e
         else:
            __SCREAMING_SNAKE_CASE   				=							pos + 1
            __SCREAMING_SNAKE_CASE   				=							text[pos:end]
            if check_simbol(lowerCamelCase     ):
               result.append("""<KIGOU>"""     )
            elif checkuae(lowerCamelCase     ):
               result.append("""<U2000U2BFF>"""     )
            else:
               for i in wd.encode("""utf-8"""     ):
                  result.append("""<|byte%d|>""" % i     )
            __SCREAMING_SNAKE_CASE   				=							end
      return result





   def   UpperCAmelCase__  (       self					:      Optional[Any]					,lowerCamelCase					:      Dict					,lowerCamelCase					:      Optional[Any]="\n"     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							[]
      __SCREAMING_SNAKE_CASE   				=							[]
      __SCREAMING_SNAKE_CASE   				=							self.ids_to_tokens[index][0]
      if word[:6] == "<|byte" and word[-2:] == "|>":
         byte_tokens.append(int(word[6:-2]     )     )
      else:
         if len(lowerCamelCase     ) > 0:
            words.append(bytearray(lowerCamelCase     ).decode("""utf-8"""					,errors="""replace"""     )     )
            __SCREAMING_SNAKE_CASE   				=							[]
         if word[:7] == "<|emoji" and word[-2:] == "|>":
            words.append(self.emoji["""emoji_inv"""][word]     )
         elif word == "<SP>":
            words.append(""" """     )
         elif word == "<BR>":
            words.append(lowerCamelCase     )
         elif word == "<TAB>":
            words.append("""\t"""     )
         elif word == "<BLOCK>":
            words.append("""▀"""     )
         elif word == "<KIGOU>":
            words.append("""ǀ"""     )
         elif word == "<U2000U2BFF>":
            words.append("""‖"""     )
         else:
            words.append(lowerCamelCase     )
      if len(lowerCamelCase     ) > 0:
         words.append(bytearray(lowerCamelCase     ).decode("""utf-8"""					,errors="""replace"""     )     )
      __SCREAMING_SNAKE_CASE   				=							"""""".join(lowerCamelCase     )
      return text





