






'''simple docstring'''







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

import regex as re

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


__A      :       int      =	logging.get_logger(__name__)

__A      :       Dict      =	{
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
}

__A      :       Dict      =	{
    'vocab_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/vocab.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/vocab.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/vocab.json',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/merges.txt',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/merges.txt',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/merges.txt',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'
        ),
    },
}

__A      :       Optional[int]      =	{
    'roberta-base': 5_1_2,
    'roberta-large': 5_1_2,
    'roberta-large-mnli': 5_1_2,
    'distilroberta-base': 5_1_2,
    'roberta-base-openai-detector': 5_1_2,
    'roberta-large-openai-detector': 5_1_2,
}


@lru_cache()
def 						_UpperCamelCase							(     ):
      __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(snake_case__							)
                  cs.append(2**8 + n							)
                  n += 1
      __A		   =      [chr(snake_case__							) for n in cs]
      return dict(zip(snake_case__							,			snake_case__							)							)


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






class 					a__    (			lowerCAmelCase__						):
     '''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    :	List[str]				,				lowercase__    :	List[Any]				,				lowercase__    :	List[str]				,				lowercase__    :	List[str]="replace"				,				lowercase__    :	Tuple="<s>"				,				lowercase__    :	Tuple="</s>"				,				lowercase__    :	str="</s>"				,				lowercase__    :	List[str]="<s>"				,				lowercase__    :	Dict="<unk>"				,				lowercase__    :	Tuple="<pad>"				,				lowercase__    :	List[Any]="<mask>"				,				lowercase__    :	Dict=False				,				**lowercase__    :	Dict				,				)  ->       Optional[int]:
           __A		   =      AddedToken(_lowerCamelCase				,				lstrip=_lowerCamelCase				,				rstrip=_lowerCamelCase					) if isinstance(_lowerCamelCase				,				_lowerCamelCase					) else bos_token
           __A		   =      AddedToken(_lowerCamelCase				,				lstrip=_lowerCamelCase				,				rstrip=_lowerCamelCase					) if isinstance(_lowerCamelCase				,				_lowerCamelCase					) else eos_token
           __A		   =      AddedToken(_lowerCamelCase				,				lstrip=_lowerCamelCase				,				rstrip=_lowerCamelCase					) if isinstance(_lowerCamelCase				,				_lowerCamelCase					) else sep_token
           __A		   =      AddedToken(_lowerCamelCase				,				lstrip=_lowerCamelCase				,				rstrip=_lowerCamelCase					) if isinstance(_lowerCamelCase				,				_lowerCamelCase					) else cls_token
           __A		   =      AddedToken(_lowerCamelCase				,				lstrip=_lowerCamelCase				,				rstrip=_lowerCamelCase					) if isinstance(_lowerCamelCase				,				_lowerCamelCase					) else unk_token
           __A		   =      AddedToken(_lowerCamelCase				,				lstrip=_lowerCamelCase				,				rstrip=_lowerCamelCase					) if isinstance(_lowerCamelCase				,				_lowerCamelCase					) else pad_token

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

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

           with open(_lowerCamelCase				,				encoding="utf-8"					) as vocab_handle:
                 __A		   =      json.load(_lowerCamelCase					)
           __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(_lowerCamelCase				,				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(_lowerCamelCase				,				range(len(_lowerCamelCase					)					)					)					)
           __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
     def     _UpperCamelCase   (self    :	Union[str, Any]					)  ->       str:
           return len(self.encoder					)






     def     _UpperCamelCase   (self    :	List[Any]					)  ->       str:
           return dict(self.encoder				,				**self.added_tokens_encoder					)






     def     _UpperCamelCase   (self    :	Dict				,				lowercase__    :	Dict					)  ->       List[Any]:

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

           if not pairs:
                 return token

           while True:
                 __A		   =      min(_lowerCamelCase				,				key=lambda lowercase__					: self.bpe_ranks.get(_lowerCamelCase				,				float("inf"					)					)					)
                 if bigram not in self.bpe_ranks:
                       break
                 __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					)
           __A		   =      word
           return word






     def     _UpperCamelCase   (self    :	List[Any]				,				lowercase__    :	Optional[int]					)  ->       List[str]:
           __A		   =      []
           for token in re.findall(self.pat				,				_lowerCamelCase					):
                 __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(_lowerCamelCase					).split(" "					)					)
           return bpe_tokens






     def     _UpperCamelCase   (self    :	Optional[Any]				,				lowercase__    :	List[Any]					)  ->       Dict:
           return self.encoder.get(_lowerCamelCase				,				self.encoder.get(self.unk_token					)					)






     def     _UpperCamelCase   (self    :	str				,				lowercase__    :	Optional[int]					)  ->       Union[str, Any]:
           return self.decoder.get(_lowerCamelCase					)






     def     _UpperCamelCase   (self    :	List[str]				,				lowercase__    :	List[str]					)  ->       Dict:
           __A		   =      """""".join(_lowerCamelCase					)
           __A		   =      bytearray([self.byte_decoder[c] for c in text]					).decode("utf-8"				,				errors=self.errors					)
           return text






     def     _UpperCamelCase   (self    :	Union[str, Any]				,				lowercase__    :	Dict				,				lowercase__    :	int = None					)  ->       Any:

           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["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"					)

           __A		   =      0
           with open(_lowerCamelCase				,				"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 lowercase__					: 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(_lowerCamelCase					) + "\n"					)
                       index += 1

           return vocab_file, merge_file






     def     _UpperCamelCase   (self    :	Any				,				lowercase__    :	str				,				lowercase__    :	Dict = None					)  ->       Dict:

           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 + sep + token_ids_a + sep






     def     _UpperCamelCase   (self    :	Any				,				lowercase__    :	Optional[int]				,				lowercase__    :	List[str] = None				,				lowercase__    :	Dict = False					)  ->       Union[str, Any]:

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

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






     def     _UpperCamelCase   (self    :	List[str]				,				lowercase__    :	int				,				lowercase__    :	str = None					)  ->       Dict:
           __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    :	List[str]				,				lowercase__    :	Tuple				,				lowercase__    :	List[Any]=False				,				**lowercase__    :	Tuple					)  ->       Any:
           __A		   =      kwargs.pop("add_prefix_space"				,				self.add_prefix_space					)
           if (is_split_into_words or add_prefix_space) and (len(_lowerCamelCase					) > 0 and not text[0].isspace()):
                 __A		   =      """ """ + text
           return (text, kwargs)










'''simple docstring'''







from cva import destroyAllWindows, imread, imshow, waitKey


def 						_UpperCamelCase							(     snake_case__							,			snake_case__							):
      __A   ,				__A		   =      img.shape[0], img.shape[1]

      def to_grayscale(snake_case__							,			snake_case__							,			snake_case__							):
            return 0.2126 * red + 0.587 * green + 0.114 * blue

      def normalize(snake_case__							):
            return min(snake_case__							,			255							)

      for i in range(snake_case__							):
            for j in range(snake_case__							):
                  __A		   =      int(to_grayscale(*img[i][j]							)							)
                  __A		   =      [
                      normalize(snake_case__							),
                      normalize(greyscale + factor							),
                      normalize(greyscale + 2 * factor							),
                  ]

      return img


if __name__ == "__main__":
       # read original image
       __A      :       Dict      =	{
           percentage: imread('image_data/lena.jpg', 1) for percentage in (1_0, 2_0, 3_0, 4_0)
       }

       for percentage, img in images.items():
              make_sepia(img, percentage)

       for percentage, img in images.items():
              imshow(F"""Original image with sepia (factor: {percentage})""", img)

       waitKey(0)
       destroyAllWindows()


