code: 
  
  
  
  
  
  
  '''simple docstring'''
  
  
  
  
  
  import json
  import os
  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
  
  UpperCAmelCase__      =							logging.get_logger(__name__)
  
  UpperCAmelCase__      =							{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}
  
  UpperCAmelCase__      =							{
      '''vocab_file''': {
          '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json''',
          '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json''',
          '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json''',
          '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json''',
          '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json''',
          '''microsoft/deberta-xlarge-mnli''': (
              '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'''
          ),
      },
      '''merges_file''': {
          '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt''',
          '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt''',
          '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt''',
          '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt''',
          '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt''',
          '''microsoft/deberta-xlarge-mnli''': (
              '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'''
          ),
      },
  }
  
  UpperCAmelCase__      =							{
      '''microsoft/deberta-base''': 5_1_2,
      '''microsoft/deberta-large''': 5_1_2,
      '''microsoft/deberta-xlarge''': 5_1_2,
      '''microsoft/deberta-base-mnli''': 5_1_2,
      '''microsoft/deberta-large-mnli''': 5_1_2,
      '''microsoft/deberta-xlarge-mnli''': 5_1_2,
  }
  
  UpperCAmelCase__      =							{
      '''microsoft/deberta-base''': {'''do_lower_case''': False},
      '''microsoft/deberta-large''': {'''do_lower_case''': False},
  }
  
  
  
  
  
  
  def 	UpperCAmelCase__(							):
  
  
  
  
  
  
  			"""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(_SCREAMING_SNAKE_CASE   )
  									cs.append(2**8 + n   )
  									n += 1
  			__A=  [chr(_SCREAMING_SNAKE_CASE   ) for n in cs]
  			return dict(zip(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE   )   )
  
  
  
  
  
  
  def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   Optional[Any]   ):
  
  
  
  
  
  
  			"""simple docstring"""
  
  
  
  
  			__A=  set()
  			__A=  word[0]
  			for char in word[1:]:
  						pairs.add((prev_char, char)   )
  						__A=  char
  			return pairs
  
  
  
  
  
  
  class 	a__				(				lowercase__      ):
  
  
  
  
  
  			'''simple docstring'''
  
  			A	:							str							= VOCAB_FILES_NAMES
  			A	:							Tuple							= PRETRAINED_VOCAB_FILES_MAP
  			A	:							int							= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  			A	:							List[str]							= ["""input_ids""", """attention_mask""", """token_type_ids"""]
  			def __init__(     self       : Union[str, Any] ,						lowerCAmelCase_       : Union[str, Any] ,						lowerCAmelCase_       : int ,						lowerCAmelCase_       : Optional[Any]="replace" ,						lowerCAmelCase_       : Optional[int]="[CLS]" ,						lowerCAmelCase_       : Optional[Any]="[SEP]" ,						lowerCAmelCase_       : Optional[int]="[SEP]" ,						lowerCAmelCase_       : int="[CLS]" ,						lowerCAmelCase_       : str="[UNK]" ,						lowerCAmelCase_       : Union[str, Any]="[PAD]" ,						lowerCAmelCase_       : Union[str, Any]="[MASK]" ,						lowerCAmelCase_       : Optional[Any]=False ,						lowerCAmelCase_       : int=False ,						**lowerCAmelCase_       : Any ,						)			->		Optional[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 ,						add_bos_token=_A ,						**_A ,						)
  						__A=  add_bos_token
  
  						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.gpt2.tokenization_gpt2.GPT2Tokenizer.vocab_size
  			def 				lowerCAmelCase    (     self       : str  )			->		List[Any]:
  						return len(self.encoder  )
  			def 				lowerCAmelCase    (     self       : Tuple  )			->		Any:
  						return dict(self.encoder ,						**self.added_tokens_encoder  )
  			def 				lowerCAmelCase    (     self       : Any ,						lowerCAmelCase_       : Union[str, Any]  )			->		str:
  						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 lowerCAmelCase_  : self.bpe_ranks.get(_A ,						float('inf'  )  )  )
  									if bigram not in self.bpe_ranks:
  												break
  									__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 				lowerCAmelCase    (     self       : List[str] ,						lowerCAmelCase_       : List[int] ,						lowerCAmelCase_       : Optional[List[int]] = None  )			->		List[int]:
  						if token_ids_a is None:
  									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
  						__A=  [self.cls_token_id]
  						__A=  [self.sep_token_id]
  						return cls + 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=_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] + ([0] * len(_A  )) + [1]
  			def 				lowerCAmelCase    (     self       : Any ,						lowerCAmelCase_       : List[int] ,						lowerCAmelCase_       : Optional[List[int]] = None  )			->		List[int]:
  						__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  ) * [0] + len(token_ids_a + sep  ) * [1]
  			def 				lowerCAmelCase    (     self       : Optional[Any] ,						lowerCAmelCase_       : Optional[int]  )			->		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 				lowerCAmelCase    (     self       : Dict ,						lowerCAmelCase_       : Optional[Any]  )			->		str:
  						return self.encoder.get(_A ,						self.encoder.get(self.unk_token  )  )
  			def 				lowerCAmelCase    (     self       : str ,						lowerCAmelCase_       : Dict  )			->		List[str]:
  						return self.decoder.get(_A  )
  			def 				lowerCAmelCase    (     self       : str ,						lowerCAmelCase_       : Dict  )			->		List[str]:
  						__A=  ''.join(_A  )
  						__A=  bytearray([self.byte_decoder[c] for c in text]  ).decode('utf-8' ,						errors=self.errors  )
  						return text
  			def 				lowerCAmelCase    (     self       : List[str] ,						lowerCAmelCase_       : str ,						lowerCAmelCase_       : Optional[str] = None  )			->		Tuple[str]:
  						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 lowerCAmelCase_  : 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 				lowerCAmelCase    (     self       : Tuple ,						lowerCAmelCase_       : Optional[Any] ,						lowerCAmelCase_       : Union[str, Any]=False ,						**lowerCAmelCase_       : Optional[int]  )			->		Dict:
  						__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 				lowerCAmelCase    (     self       : List[Any] ,						lowerCAmelCase_       : "Conversation"  )			->		List[int]:
  						__A=  []
  						for is_user, text in conversation.iter_texts():
  									input_ids.extend(self.encode(_A ,						add_special_tokens=_A  ) + [self.eos_token_id]  )
  						if len(_A  ) > self.model_max_length:
  									__A=  input_ids[-self.model_max_length :]
  						return input_ids
  
  
  
  
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()
  
  
  
  