





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

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


lowerCAmelCase_   =   logging.get_logger(__name__)

lowerCAmelCase_   =   {
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
}

lowerCAmelCase_   =   {
    "vocab_file": {
        "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json",
    },
    "merges_file": {"microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt"},
}

lowerCAmelCase_   =   {
    "microsoft/biogpt": 1_0_2_4,
}




def 						A_			(  lowercase_  )			->						Dict:
       _snake_case      :							int     				=						set()
       _snake_case      :							Any     				=						word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)  )
              _snake_case      :							List[str]     				=						char
       return pairs

class 				A    (__UpperCAmelCase				):
      _SCREAMING_SNAKE_CASE					=							VOCAB_FILES_NAMES
      _SCREAMING_SNAKE_CASE					=							PRETRAINED_VOCAB_FILES_MAP
      _SCREAMING_SNAKE_CASE					=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _SCREAMING_SNAKE_CASE					=							["""input_ids""", """attention_mask"""]



      def __init__(					self     ,  lowercase_     ,  lowercase_     ,  lowercase_="<unk>"     ,  lowercase_="<s>"     ,  lowercase_="</s>"     ,  lowercase_="</s>"     ,  lowercase_="<pad>"     ,  **lowercase_     ,  )      ->   Optional[int]:



             '''simple docstring'''

             super().__init__(
                 bos_token=lowercase_     ,  eos_token=lowercase_     ,  sep_token=lowercase_     ,  unk_token=lowercase_     ,  pad_token=lowercase_     ,  **lowercase_     ,  )

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

             _snake_case      :							Optional[int]     				=						'''en'''
             _snake_case      :							Optional[int]     				=						sacremoses
             # cache of sm.MosesTokenizer instance
             _snake_case      :							Optional[int]     				=						{}
             _snake_case      :							List[str]     				=						{}
             with open(lowercase_     ,  encoding='''utf-8'''					) as vocab_handle:
                    _snake_case      :							List[Any]     				=						json.load(lowercase_					)
             _snake_case      :							Dict     				=						{v: k for k, v in self.encoder.items()}
             with open(lowercase_     ,  encoding='''utf-8'''					) as merges_handle:
                    _snake_case      :							Optional[int]     				=						merges_handle.read().split('''\n'''					)[:-1]
             _snake_case      :							Optional[Any]     				=						[tuple(merge.split()[:2]					) for merge in merges]
             _snake_case      :							List[str]     				=						dict(zip(lowercase_     ,  range(len(lowercase_					)					)					)					)
             _snake_case      :							Any     				=						{}



      @property
      def    __a (					self					)      ->   List[Any]:



             '''simple docstring'''

             return len(self.encoder					)



      def    __a (					self					)      ->   str:



             '''simple docstring'''

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



      def    __a (					self     ,  lowercase_     ,  lowercase_					)      ->   Optional[int]:



             '''simple docstring'''

             if lang not in self.cache_moses_tokenizer:
                    _snake_case      :							Union[str, Any]     				=						self.sm.MosesTokenizer(lang=lowercase_					)
                    _snake_case      :							List[Any]     				=						moses_tokenizer
             return self.cache_moses_tokenizer[lang].tokenize(
                 lowercase_     ,  aggressive_dash_splits=lowercase_     ,  return_str=lowercase_     ,  escape=lowercase_					)



      def    __a (					self     ,  lowercase_     ,  lowercase_					)      ->   List[Any]:



             '''simple docstring'''

             if lang not in self.cache_moses_detokenizer:
                    _snake_case      :							Dict     				=						self.sm.MosesDetokenizer(lang=lowercase_					)
                    _snake_case      :							List[Any]     				=						moses_detokenizer
             return self.cache_moses_detokenizer[lang].detokenize(lowercase_					)



      def    __a (					self     ,  lowercase_					)      ->   List[str]:



             '''simple docstring'''

             _snake_case      :							List[str]     				=						tuple(token[:-1]					) + (token[-1] + '''</w>''',)
             if token in self.cache:
                    return self.cache[token]
             _snake_case      :							List[Any]     				=						get_pairs(lowercase_					)

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

             while True:
                    _snake_case      :							Union[str, Any]     				=						min(lowercase_     ,  key=lambda lowercase_					: self.bpe_ranks.get(lowercase_     ,  float('''inf'''					)					)					)
                    if bigram not in self.bpe_ranks:
                           break
                    _snake_case      :							Optional[Any]     				=						bigram
                    _snake_case      :							Tuple     				=						[]
                    _snake_case      :							str     				=						0
                    while i < len(lowercase_					):
                           try:
                                  _snake_case      :							Optional[Any]     				=						word.index(lowercase_     ,  lowercase_					)
                           except ValueError:
                                  new_word.extend(word[i:]					)
                                  break
                           else:
                                  new_word.extend(word[i:j]					)
                                  _snake_case      :							Optional[int]     				=						j

                           if word[i] == first and i < len(lowercase_					) - 1 and word[i + 1] == second:
                                  new_word.append(first + second					)
                                  i += 2
                           else:
                                  new_word.append(word[i]					)
                                  i += 1
                    _snake_case      :							int     				=						tuple(lowercase_					)
                    _snake_case      :							List[str]     				=						new_word
                    if len(lowercase_					) == 1:
                           break
                    else:
                           _snake_case      :							Optional[Any]     				=						get_pairs(lowercase_					)
             _snake_case      :							int     				=						''' '''.join(lowercase_					)
             if word == "\n  </w>":
                    _snake_case      :							int     				=						'''\n</w>'''
             _snake_case      :							Any     				=						word
             return word



      def    __a (					self     ,  lowercase_     ,  lowercase_=False					)      ->   List[Any]:



             '''simple docstring'''

             if bypass_tokenizer:
                    _snake_case      :							Dict     				=						text.split()
             else:
                    _snake_case      :							Any     				=						self.moses_tokenize(lowercase_     ,  self.lang					)

             _snake_case      :							Any     				=						[]
             for token in text:
                    if token:
                           split_tokens.extend(list(self.bpe(lowercase_					).split(''' '''					)					)					)

             return split_tokens



      def    __a (					self     ,  lowercase_					)      ->   str:



             '''simple docstring'''

             return self.encoder.get(lowercase_     ,  self.encoder.get(self.unk_token					)					)



      def    __a (					self     ,  lowercase_					)      ->   Optional[int]:



             '''simple docstring'''

             return self.decoder.get(lowercase_     ,  self.unk_token					)



      def    __a (					self     ,  lowercase_					)      ->   List[str]:



             '''simple docstring'''

             _snake_case      :							Dict     				=						[t.replace(''' '''     ,  ''''''					).replace('''</w>'''     ,  ''' '''					) for t in tokens]
             _snake_case      :							str     				=						''''''.join(lowercase_					).split()
             # detokenize
             _snake_case      :							Union[str, Any]     				=						self.moses_detokenize(lowercase_     ,  self.lang					)
             return text



      def    __a (					self     ,  lowercase_     ,  lowercase_ = None					)      ->   List[int]:



             '''simple docstring'''

             if token_ids_a is None:
                    return [self.sep_token_id] + token_ids_a
             _snake_case      :							Any     				=						[self.sep_token_id]
             return sep + token_ids_a + sep + token_ids_a



      def    __a (					self     ,  lowercase_     ,  lowercase_ = None     ,  lowercase_ = False					)      ->   List[int]:



             '''simple docstring'''

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



      def    __a (					self     ,  lowercase_     ,  lowercase_ = None					)      ->   List[int]:



             '''simple docstring'''

             _snake_case      :							str     				=						[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    __a (					self     ,  lowercase_     ,  lowercase_ = None					)      ->   Tuple[str]:



             '''simple docstring'''

             if not os.path.isdir(lowercase_					):
                    logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''					)
                    return
             _snake_case      :							Any     				=						os.path.join(
                 lowercase_     ,  (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)
             _snake_case      :							List[str]     				=						os.path.join(
                 lowercase_     ,  (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']					)

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

             _snake_case      :							Optional[Any]     				=						0
             with open(lowercase_     ,  '''w'''     ,  encoding='''utf-8'''					) as writer:
                    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!'''					)
                                  _snake_case      :							List[str]     				=						token_index
                           writer.write(''' '''.join(lowercase_					) + '''\n'''					)
                           index += 1

             return vocab_file, merge_file



      def __getstate__(					self					)      ->   List[str]:



             '''simple docstring'''

             _snake_case      :							List[str]     				=						self.__dict__.copy()
             _snake_case      :							Any     				=						None
             return state



      def __setstate__(					self     ,  lowercase_					)      ->   List[str]:



             '''simple docstring'''

             _snake_case      :							Optional[Any]     				=						d

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

             _snake_case      :							Optional[int]     				=						sacremoses













import cva
import numpy as np




def 						A_			(  lowercase_      ,		lowercase_      ,		lowercase_      ,		lowercase_  )			->						int:

       try:
              return int(image[x_coordinate][y_coordinate] >= center  )
       except (IndexError, TypeError):
              return 0




def 						A_			(  lowercase_      ,		lowercase_      ,		lowercase_  )			->						int:
       _snake_case      :							List[str]     				=						image[x_coordinate][y_coordinate]
       _snake_case      :							List[str]     				=						[1, 2, 4, 8, 16, 32, 64, 128]

       # skip get_neighbors_pixel if center is null
       if center is None:
              return 0

       # Starting from the top right, assigning value to pixels clockwise
       _snake_case      :							Any     				=						[
           get_neighbors_pixel(lowercase_      ,		x_coordinate - 1      ,		y_coordinate + 1      ,		lowercase_  ),
           get_neighbors_pixel(lowercase_      ,		lowercase_      ,		y_coordinate + 1      ,		lowercase_  ),
           get_neighbors_pixel(lowercase_      ,		x_coordinate - 1      ,		lowercase_      ,		lowercase_  ),
           get_neighbors_pixel(lowercase_      ,		x_coordinate + 1      ,		y_coordinate + 1      ,		lowercase_  ),
           get_neighbors_pixel(lowercase_      ,		x_coordinate + 1      ,		lowercase_      ,		lowercase_  ),
           get_neighbors_pixel(lowercase_      ,		x_coordinate + 1      ,		y_coordinate - 1      ,		lowercase_  ),
           get_neighbors_pixel(lowercase_      ,		lowercase_      ,		y_coordinate - 1      ,		lowercase_  ),
           get_neighbors_pixel(lowercase_      ,		x_coordinate - 1      ,		y_coordinate - 1      ,		lowercase_  ),
       ]

       # Converting the binary value to decimal.
       return sum(
           binary_value * power for binary_value, power in zip(lowercase_      ,		lowercase_  )  )


if __name__ == "__main__":
   # Reading the image and converting it to grayscale.
   lowerCAmelCase_   =   cva.imread(
       "digital_image_processing/image_data/lena.jpg", cva.IMREAD_GRAYSCALE
   )

   # Create a numpy array as the same height and width of read image
   lowerCAmelCase_   =   np.zeros((image.shape[0], image.shape[1]))

   # Iterating through the image and calculating the
   # local binary pattern value for each pixel.
   for i in range(0, image.shape[0]):
      for j in range(0, image.shape[1]):
         lowerCAmelCase_   =   local_binary_value(image, i, j)

   cva.imshow("local binary pattern", lbp_image)
   cva.waitKey(0)
   cva.destroyAllWindows()






