code: 
  
  
  '''simple docstring'''
  
  
  
  
  
  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__      =							logging.get_logger(__name__)
  
  UpperCAmelCase__      =							{
      '''src_vocab_file''': '''vocab-src.json''',
      '''tgt_vocab_file''': '''vocab-tgt.json''',
      '''merges_file''': '''merges.txt''',
  }
  
  UpperCAmelCase__      =							{
      '''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__      =							{'''stas/tiny-wmt19-en-de''': 1_0_2_4}
  UpperCAmelCase__      =							{
      '''stas/tiny-wmt19-en-de''': {
          '''langs''': ['''en''', '''de'''],
          '''model_max_length''': 1_0_2_4,
          '''special_tokens_map_file''': None,
          '''full_tokenizer_file''': None,
      }
  }
  
  
  
  
  
  
  def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   Tuple   ):
  
  
  
  
  
  
  			"""simple docstring"""
  
  
  
  
  			__A=  set()
  			__A=  word[0]
  			for char in word[1:]:
  						pairs.add((prev_char, char)   )
  						__A=  char
  			return pairs
  
  
  
  
  
  
  def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   Any   ):
  
  
  
  
  
  
  			"""simple docstring"""
  
  
  
  
  			__A=  text.replace('，',','   )
  			__A=  re.sub(r'。\s*','. ',_SCREAMING_SNAKE_CASE   )
  			__A=  text.replace('、',','   )
  			__A=  text.replace('”','"'   )
  			__A=  text.replace('“','"'   )
  			__A=  text.replace('∶',':'   )
  			__A=  text.replace('：',':'   )
  			__A=  text.replace('？','?'   )
  			__A=  text.replace('《','"'   )
  			__A=  text.replace('》','"'   )
  			__A=  text.replace('）',')'   )
  			__A=  text.replace('！','!'   )
  			__A=  text.replace('（','('   )
  			__A=  text.replace('；',';'   )
  			__A=  text.replace('１','1'   )
  			__A=  text.replace('」','"'   )
  			__A=  text.replace('「','"'   )
  			__A=  text.replace('０','0'   )
  			__A=  text.replace('３','3'   )
  			__A=  text.replace('２','2'   )
  			__A=  text.replace('５','5'   )
  			__A=  text.replace('６','6'   )
  			__A=  text.replace('９','9'   )
  			__A=  text.replace('７','7'   )
  			__A=  text.replace('８','8'   )
  			__A=  text.replace('４','4'   )
  			__A=  re.sub(r'．\s*','. ',_SCREAMING_SNAKE_CASE   )
  			__A=  text.replace('～','~'   )
  			__A=  text.replace('’','\''   )
  			__A=  text.replace('…','...'   )
  			__A=  text.replace('━','-'   )
  			__A=  text.replace('〈','<'   )
  			__A=  text.replace('〉','>'   )
  			__A=  text.replace('【','['   )
  			__A=  text.replace('】',']'   )
  			__A=  text.replace('％','%'   )
  			return text
  
  
  
  
  
  
  def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   List[Any]   ):
  
  
  
  
  
  
  			"""simple docstring"""
  
  
  
  
  			__A=  []
  			for char in text:
  						__A=  unicodedata.category(_SCREAMING_SNAKE_CASE   )
  						if cat.startswith('C'   ):
  									continue
  						output.append(_SCREAMING_SNAKE_CASE   )
  			return "".join(_SCREAMING_SNAKE_CASE   )
  
  
  
  
  
  
  class 	a__				(				a_      ):
  
  
  
  
  
  			'''simple docstring'''
  
  			A	:							Optional[int]							= VOCAB_FILES_NAMES
  			A	:							List[str]							= PRETRAINED_VOCAB_FILES_MAP
  			A	:							Optional[int]							= PRETRAINED_INIT_CONFIGURATION
  			A	:							Union[str, Any]							= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  			A	:							str							= ['''input_ids''', '''attention_mask''']
  			def __init__(     self       : Optional[int] ,						lowerCAmelCase_       : Optional[int]=None ,						lowerCAmelCase_       : Tuple=None ,						lowerCAmelCase_       : str=None ,						lowerCAmelCase_       : Union[str, Any]=None ,						lowerCAmelCase_       : Union[str, Any]=False ,						lowerCAmelCase_       : Union[str, Any]="<unk>" ,						lowerCAmelCase_       : Union[str, Any]="<s>" ,						lowerCAmelCase_       : List[Any]="</s>" ,						lowerCAmelCase_       : Tuple="<pad>" ,						**lowerCAmelCase_       : Dict ,						)			->		int:
  						super().__init__(
  						    langs=lowerCAmelCase_ ,						src_vocab_file=lowerCAmelCase_ ,						tgt_vocab_file=lowerCAmelCase_ ,						merges_file=lowerCAmelCase_ ,						do_lower_case=lowerCAmelCase_ ,						unk_token=lowerCAmelCase_ ,						bos_token=lowerCAmelCase_ ,						sep_token=lowerCAmelCase_ ,						pad_token=lowerCAmelCase_ ,						**lowerCAmelCase_ ,						)
  
  						try:
  									import sacremoses
  						except ImportError:
  									raise ImportError(
  									    'You need to install sacremoses to use XLMTokenizer. '
  									    'See https://pypi.org/project/sacremoses/ for installation.'  )
  
  						__A=  sacremoses
  
  						__A=  src_vocab_file
  						__A=  tgt_vocab_file
  						__A=  merges_file
  						__A=  do_lower_case
  
  						# cache of sm.MosesPunctNormalizer instance
  						__A=  {}
  						# cache of sm.MosesTokenizer instance
  						__A=  {}
  						__A=  {}
  
  						if langs and len(lowerCAmelCase_  ) == 2:
  									__A,  __A=  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(lowerCAmelCase_ ,						encoding='utf-8'  ) as src_vocab_handle:
  									__A=  json.load(lowerCAmelCase_  )
  						with open(lowerCAmelCase_ ,						encoding='utf-8'  ) as tgt_vocab_handle:
  									__A=  json.load(lowerCAmelCase_  )
  									__A=  {v: k for k, v in tgt_vocab.items()}
  						with open(lowerCAmelCase_ ,						encoding='utf-8'  ) as merges_handle:
  									__A=  merges_handle.read().split('\n'  )[:-1]
  						__A=  [tuple(merge.split()[:2]  ) for merge in merges]
  						__A=  dict(zip(lowerCAmelCase_ ,						range(len(lowerCAmelCase_  )  )  )  )
  						__A=  {}
  			def 				lowerCAmelCase    (     self       : List[str]  )			->		Dict[str, int]:
  						return self.get_src_vocab()
  			@property
  			def 				lowerCAmelCase    (     self       : List[Any]  )			->		int:
  						return self.src_vocab_size
  			def 				lowerCAmelCase    (     self       : Optional[Any] ,						lowerCAmelCase_       : Any ,						lowerCAmelCase_       : List[str]  )			->		List[str]:
  						if lang not in self.cache_moses_punct_normalizer:
  									__A=  self.sm.MosesPunctNormalizer(lang=lowerCAmelCase_  )
  									__A=  punct_normalizer
  						return self.cache_moses_punct_normalizer[lang].normalize(lowerCAmelCase_  )
  			def 				lowerCAmelCase    (     self       : str ,						lowerCAmelCase_       : Any ,						lowerCAmelCase_       : str  )			->		Union[str, Any]:
  						if lang not in self.cache_moses_tokenizer:
  									__A=  self.sm.MosesTokenizer(lang=lowerCAmelCase_  )
  									__A=  moses_tokenizer
  						return self.cache_moses_tokenizer[lang].tokenize(
  						    lowerCAmelCase_ ,						aggressive_dash_splits=lowerCAmelCase_ ,						return_str=lowerCAmelCase_ ,						escape=lowerCAmelCase_  )
  			def 				lowerCAmelCase    (     self       : Tuple ,						lowerCAmelCase_       : Tuple ,						lowerCAmelCase_       : str  )			->		str:
  						if lang not in self.cache_moses_detokenizer:
  									__A=  self.sm.MosesDetokenizer(lang=lowerCAmelCase_  )
  									__A=  moses_detokenizer
  						return self.cache_moses_detokenizer[lang].detokenize(lowerCAmelCase_  )
  			def 				lowerCAmelCase    (     self       : Any ,						lowerCAmelCase_       : Tuple ,						lowerCAmelCase_       : Optional[int]  )			->		Any:
  						__A=  replace_unicode_punct(lowerCAmelCase_  )
  						__A=  self.moses_punct_norm(lowerCAmelCase_ ,						lowerCAmelCase_  )
  						__A=  remove_non_printing_char(lowerCAmelCase_  )
  						return text
  			@property
  			def 				lowerCAmelCase    (     self       : Dict  )			->		str:
  						return len(self.encoder  )
  			@property
  			def 				lowerCAmelCase    (     self       : List[Any]  )			->		Tuple:
  						return len(self.decoder  )
  			def 				lowerCAmelCase    (     self       : Union[str, Any]  )			->		List[Any]:
  						return dict(self.encoder ,						**self.added_tokens_encoder  )
  			def 				lowerCAmelCase    (     self       : Dict  )			->		str:
  						return dict(self.decoder ,						**self.added_tokens_decoder  )
  			def 				lowerCAmelCase    (     self       : int ,						lowerCAmelCase_       : List[str]  )			->		Tuple:
  						__A=  tuple(token[:-1]  ) + (token[-1] + '</w>',)
  						if token in self.cache:
  									return self.cache[token]
  						__A=  get_pairs(lowerCAmelCase_  )
  
  						if not pairs:
  									return token + "</w>"
  
  						while True:
  									__A=  min(lowerCAmelCase_ ,						key=lambda lowerCAmelCase_  : self.bpe_ranks.get(lowerCAmelCase_ ,						float('inf'  )  )  )
  									if bigram not in self.bpe_ranks:
  												break
  									__A,  __A=  bigram
  									__A=  []
  									__A=  0
  									while i < len(lowerCAmelCase_  ):
  												try:
  															__A=  word.index(lowerCAmelCase_ ,						lowerCAmelCase_  )
  												except ValueError:
  															new_word.extend(word[i:]  )
  															break
  												else:
  															new_word.extend(word[i:j]  )
  															__A=  j
  
  												if word[i] == first and i < len(lowerCAmelCase_  ) - 1 and word[i + 1] == second:
  															new_word.append(first + second  )
  															i += 2
  												else:
  															new_word.append(word[i]  )
  															i += 1
  									__A=  tuple(lowerCAmelCase_  )
  									__A=  new_word
  									if len(lowerCAmelCase_  ) == 1:
  												break
  									else:
  												__A=  get_pairs(lowerCAmelCase_  )
  						__A=  ' '.join(lowerCAmelCase_  )
  						if word == "\n  </w>":
  									__A=  '\n</w>'
  						__A=  word
  						return word
  			def 				lowerCAmelCase    (     self       : Dict ,						lowerCAmelCase_       : Tuple ,						lowerCAmelCase_       : Optional[int]="en" ,						lowerCAmelCase_       : Tuple=False  )			->		Optional[int]:
  						__A=  self.src_lang
  
  						if self.do_lower_case:
  									__A=  text.lower()
  
  						if bypass_tokenizer:
  									__A=  text.split()
  						else:
  									__A=  self.moses_pipeline(lowerCAmelCase_ ,						lang=lowerCAmelCase_  )
  									__A=  self.moses_tokenize(lowerCAmelCase_ ,						lang=lowerCAmelCase_  )
  
  						__A=  []
  						for token in text:
  									if token:
  												split_tokens.extend(list(self.bpe(lowerCAmelCase_  ).split(' '  )  )  )
  
  						return split_tokens
  			def 				lowerCAmelCase    (     self       : Tuple ,						lowerCAmelCase_       : Optional[int]  )			->		str:
  						return self.encoder.get(lowerCAmelCase_ ,						self.encoder.get(self.unk_token  )  )
  			def 				lowerCAmelCase    (     self       : List[Any] ,						lowerCAmelCase_       : Dict  )			->		int:
  						return self.decoder.get(lowerCAmelCase_ ,						self.unk_token  )
  			def 				lowerCAmelCase    (     self       : Union[str, Any] ,						lowerCAmelCase_       : List[Any]  )			->		int:
  						__A=  [t.replace(' ' ,						''  ).replace('</w>' ,						' '  ) for t in tokens]
  						__A=  ''.join(lowerCAmelCase_  ).split()
  						# detokenize
  						__A=  self.moses_detokenize(lowerCAmelCase_ ,						self.tgt_lang  )
  						return text
  			def 				lowerCAmelCase    (     self       : str ,						lowerCAmelCase_       : List[int] ,						lowerCAmelCase_       : Optional[List[int]] = None  )			->		List[int]:
  						__A=  [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       : Optional[int] ,						lowerCAmelCase_       : List[int] ,						lowerCAmelCase_       : Optional[List[int]] = None ,						lowerCAmelCase_       : bool = False  )			->		List[int]:
  
  						if already_has_special_tokens:
  									return super().get_special_tokens_mask(
  									    token_ids_a=lowerCAmelCase_ ,						token_ids_a=lowerCAmelCase_ ,						already_has_special_tokens=lowerCAmelCase_  )
  						# no bos used in fairseq
  						if token_ids_a is not None:
  									return ([0] * len(lowerCAmelCase_  )) + [1] + ([0] * len(lowerCAmelCase_  )) + [1]
  						return ([0] * len(lowerCAmelCase_  )) + [1]
  			def 				lowerCAmelCase    (     self       : Dict ,						lowerCAmelCase_       : List[int] ,						lowerCAmelCase_       : Optional[List[int]] = None  )			->		List[int]:
  						__A=  [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       : List[str] ,						lowerCAmelCase_       : str ,						lowerCAmelCase_       : Optional[str] = None  )			->		Tuple[str]:
  						if not os.path.isdir(lowerCAmelCase_  ):
  									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""  )
  									return
  
  						__A=  os.path.join(
  						    lowerCAmelCase_ ,						(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['src_vocab_file']  )
  						__A=  os.path.join(
  						    lowerCAmelCase_ ,						(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['tgt_vocab_file']  )
  						__A=  os.path.join(
  						    lowerCAmelCase_ ,						(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']  )
  
  						with open(lowerCAmelCase_ ,						'w' ,						encoding='utf-8'  ) as f:
  									f.write(json.dumps(self.encoder ,						indent=2 ,						sort_keys=lowerCAmelCase_ ,						ensure_ascii=lowerCAmelCase_  ) + '\n'  )
  
  						with open(lowerCAmelCase_ ,						'w' ,						encoding='utf-8'  ) as f:
  									__A=  {v: k for k, v in self.decoder.items()}
  									f.write(json.dumps(lowerCAmelCase_ ,						indent=2 ,						sort_keys=lowerCAmelCase_ ,						ensure_ascii=lowerCAmelCase_  ) + '\n'  )
  
  						__A=  0
  						with open(lowerCAmelCase_ ,						'w' ,						encoding='utf-8'  ) as writer:
  									for bpe_tokens, token_index in sorted(self.bpe_ranks.items() ,						key=lambda lowerCAmelCase_  : 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!'  )
  															__A=  token_index
  												writer.write(' '.join(lowerCAmelCase_  ) + '\n'  )
  												index += 1
  
  						return src_vocab_file, tgt_vocab_file, merges_file
  			def __getstate__(     self       : Union[str, Any]  )			->		str:
  						__A=  self.__dict__.copy()
  						__A=  None
  						return state
  
  			def __setstate__(     self       : Tuple ,						lowerCAmelCase_       : Union[str, Any]  )			->		str:
  						__A=  d
  
  						try:
  									import sacremoses
  						except ImportError:
  									raise ImportError(
  									    'You need to install sacremoses to use XLMTokenizer. '
  									    'See https://pypi.org/project/sacremoses/ for installation.'  )
  
  						__A=  sacremoses
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  
  
  
  
  import numpy as np
  from cva import destroyAllWindows, imread, imshow, waitKey
  class 	a__				:
  
  
  
  
  
  			'''simple docstring'''
  
  			def __init__(     self       : Dict ,						lowerCAmelCase_       : Optional[Any] ,						lowerCAmelCase_       : int  )			->		Optional[int]:
  						__A=  0
  						# max greyscale value for #FFFFFF
  						__A=  int(self.get_greyscale(255 ,						255 ,						255  )  )
  
  						if not self.min_threshold < threshold < self.max_threshold:
  									__A=  F"""Factor value should be from 0 to {self.max_threshold}"""
  									raise ValueError(lowerCAmelCase_  )
  
  						__A=  input_img
  						__A=  threshold
  						__A,  __A=  self.input_img.shape[1], self.input_img.shape[0]
  
  						# error table size (+4 columns and +1 row) greater than input image because of
  						# lack of if statements
  						__A=  [
  						    [0 for _ in range(self.height + 4  )] for __ in range(self.width + 1  )
  						]
  						__A=  np.ones((self.width, self.height, 3) ,						np.uinta  ) * 255
  			@classmethod
  			def 				lowerCAmelCase    (     cls       : Tuple ,						lowerCAmelCase_       : int ,						lowerCAmelCase_       : int ,						lowerCAmelCase_       : int  )			->		float:
  						return 0.1_14 * blue + 0.5_87 * green + 0.21_26 * red
  
  			def 				lowerCAmelCase    (     self       : str  )			->		None:
  						for y in range(self.height  ):
  									for x in range(self.width  ):
  												__A=  int(self.get_greyscale(*self.input_img[y][x]  )  )
  												if self.threshold > greyscale + self.error_table[y][x]:
  															__A=  (0, 0, 0)
  															__A=  greyscale + self.error_table[x][y]
  												else:
  															__A=  (255, 255, 255)
  															__A=  greyscale + self.error_table[x][y] - 255
  												self.error_table[y][x + 1] += int(8 / 32 * current_error  )
  												self.error_table[y][x + 2] += int(4 / 32 * current_error  )
  												self.error_table[y + 1][x] += int(8 / 32 * current_error  )
  												self.error_table[y + 1][x + 1] += int(4 / 32 * current_error  )
  												self.error_table[y + 1][x + 2] += int(2 / 32 * current_error  )
  												self.error_table[y + 1][x - 1] += int(4 / 32 * current_error  )
  												self.error_table[y + 1][x - 2] += int(2 / 32 * current_error  )
  
  
  if __name__ == "__main__":
  					# create Burke's instances with original images in greyscale
  					UpperCAmelCase__      =							[
  					    Burkes(imread('''image_data/lena.jpg''', 1), threshold)
  					    for threshold in (1, 1_2_6, 1_3_0, 1_4_0)
  					]
  
  					for burkes in burkes_instances:
  										burkes.process()
  
  					for burkes in burkes_instances:
  										imshow(
  										    F"""Original image with dithering threshold: {burkes.threshold}""",
  										    burkes.output_img,
  										)
  
  					waitKey(0)
  					destroyAllWindows()
  
  
  
  