



'''simple docstring'''


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer


_lowerCamelCase      :			str       =      {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

_lowerCamelCase      :			Optional[int]       =      {
    "vocab_file": {
        "google/electra-small-generator": (
            "https://huggingface.co/google/electra-small-generator/resolve/main/vocab.txt"
        ),
        "google/electra-base-generator": "https://huggingface.co/google/electra-base-generator/resolve/main/vocab.txt",
        "google/electra-large-generator": (
            "https://huggingface.co/google/electra-large-generator/resolve/main/vocab.txt"
        ),
        "google/electra-small-discriminator": (
            "https://huggingface.co/google/electra-small-discriminator/resolve/main/vocab.txt"
        ),
        "google/electra-base-discriminator": (
            "https://huggingface.co/google/electra-base-discriminator/resolve/main/vocab.txt"
        ),
        "google/electra-large-discriminator": (
            "https://huggingface.co/google/electra-large-discriminator/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "google/electra-small-generator": (
            "https://huggingface.co/google/electra-small-generator/resolve/main/tokenizer.json"
        ),
        "google/electra-base-generator": (
            "https://huggingface.co/google/electra-base-generator/resolve/main/tokenizer.json"
        ),
        "google/electra-large-generator": (
            "https://huggingface.co/google/electra-large-generator/resolve/main/tokenizer.json"
        ),
        "google/electra-small-discriminator": (
            "https://huggingface.co/google/electra-small-discriminator/resolve/main/tokenizer.json"
        ),
        "google/electra-base-discriminator": (
            "https://huggingface.co/google/electra-base-discriminator/resolve/main/tokenizer.json"
        ),
        "google/electra-large-discriminator": (
            "https://huggingface.co/google/electra-large-discriminator/resolve/main/tokenizer.json"
        ),
    },
}

_lowerCamelCase      :			Optional[int]       =      {
    "google/electra-small-generator": 512,
    "google/electra-base-generator": 512,
    "google/electra-large-generator": 512,
    "google/electra-small-discriminator": 512,
    "google/electra-base-discriminator": 512,
    "google/electra-large-discriminator": 512,
}

_lowerCamelCase      :			Any       =      {
    "google/electra-small-generator": {"do_lower_case": True},
    "google/electra-base-generator": {"do_lower_case": True},
    "google/electra-large-generator": {"do_lower_case": True},
    "google/electra-small-discriminator": {"do_lower_case": True},
    "google/electra-base-discriminator": {"do_lower_case": True},
    "google/electra-large-discriminator": {"do_lower_case": True},
}

class 					SCREAMING_SNAKE_CASE					(    __A						):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE          =    VOCAB_FILES_NAMES
    _SCREAMING_SNAKE_CASE          =    PRETRAINED_VOCAB_FILES_MAP
    _SCREAMING_SNAKE_CASE          =    PRETRAINED_INIT_CONFIGURATION
    _SCREAMING_SNAKE_CASE          =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _SCREAMING_SNAKE_CASE          =    ElectraTokenizer






    def __init__(    self :   Optional[int]    ,		UpperCamelCase__ :   Any=None    ,		UpperCamelCase__ :   str=None    ,		UpperCamelCase__ :   List[Any]=True    ,		UpperCamelCase__ :   str="[UNK]"    ,		UpperCamelCase__ :   Dict="[SEP]"    ,		UpperCamelCase__ :   List[Any]="[PAD]"    ,		UpperCamelCase__ :   List[Any]="[CLS]"    ,		UpperCamelCase__ :   Union[str, Any]="[MASK]"    ,		UpperCamelCase__ :   Optional[Any]=True    ,		UpperCamelCase__ :   int=None    ,		**UpperCamelCase__ :   Dict    ,		):


       """simple docstring"""







       super().__init__(
           UpperCamelCase__    ,		tokenizer_file=UpperCamelCase__    ,		do_lower_case=UpperCamelCase__    ,		unk_token=UpperCamelCase__    ,		sep_token=UpperCamelCase__    ,		pad_token=UpperCamelCase__    ,		cls_token=UpperCamelCase__    ,		mask_token=UpperCamelCase__    ,		tokenize_chinese_chars=UpperCamelCase__    ,		strip_accents=UpperCamelCase__    ,		**UpperCamelCase__    ,		)

       UpperCamelCase      							=    json.loads(self.backend_tokenizer.normalizer.__getstate__()					)
       if (
           normalizer_state.get('lowercase'    ,		UpperCamelCase__					) != do_lower_case
           or normalizer_state.get('strip_accents'    ,		UpperCamelCase__					) != strip_accents
           or normalizer_state.get('handle_chinese_chars'    ,		UpperCamelCase__					) != tokenize_chinese_chars
       ):
          UpperCamelCase      							=    getattr(UpperCamelCase__    ,		normalizer_state.pop('type'					)					)
          UpperCamelCase      							=    do_lower_case
          UpperCamelCase      							=    strip_accents
          UpperCamelCase      							=    tokenize_chinese_chars
          UpperCamelCase      							=    normalizer_class(**UpperCamelCase__					)

       UpperCamelCase      							=    do_lower_case






    def 					A			(    self :   List[Any]    ,		UpperCamelCase__ :   Optional[Any]    ,		UpperCamelCase__ :   Tuple=None					):


       """simple docstring"""







       UpperCamelCase      							=    [self.cls_token_id] + token_ids_a + [self.sep_token_id]

       if token_ids_a:
          output += token_ids_a + [self.sep_token_id]

       return output






    def 					A			(    self :   int    ,		UpperCamelCase__ :   List[int]    ,		UpperCamelCase__ :   Optional[List[int]] = None					):


       """simple docstring"""







       UpperCamelCase      							=    [self.sep_token_id]
       UpperCamelCase      							=    [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 					A			(    self :   int    ,		UpperCamelCase__ :   str    ,		UpperCamelCase__ :   Optional[str] = None					):


       """simple docstring"""







       UpperCamelCase      							=    self._tokenizer.model.save(UpperCamelCase__    ,		name=UpperCamelCase__					)
       return tuple(UpperCamelCase__					)









'''simple docstring'''



import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
SCREAMING_SNAKE_CASE							=						{
    'E': 12.70,
    'T': 9.06,
    'A': 8.17,
    'O': 7.51,
    'I': 6.97,
    'N': 6.75,
    'S': 6.33,
    'H': 6.09,
    'R': 5.99,
    'D': 4.25,
    'L': 4.03,
    'C': 2.78,
    'U': 2.76,
    'M': 2.41,
    'W': 2.36,
    'F': 2.23,
    'G': 2.02,
    'Y': 1.97,
    'P': 1.93,
    'B': 1.29,
    'V': 0.98,
    'K': 0.77,
    'J': 0.15,
    'X': 0.15,
    'Q': 0.10,
    'Z': 0.07,
}
SCREAMING_SNAKE_CASE							=						'ETAOINSHRDLCUMWFGYPBVKJXQZ'
SCREAMING_SNAKE_CASE							=						'ABCDEFGHIJKLMNOPQRSTUVWXYZ'


def 				lowercase_					(     __A			:							str      )							->   dict[str, int]:



 """simple docstring"""




 lowercase       : List[str]						={letter: 0 for letter in string.ascii_uppercase}
 for letter in message.upper():
  if letter in LETTERS:
   letter_count[letter] += 1

 return letter_count


def 				lowercase_					(     __A			:							tuple      )							->   str:



 """simple docstring"""




 return x[0]


def 				lowercase_					(     __A			:							str      )							->   str:



 """simple docstring"""




 lowercase       : Optional[Any]						=get_letter_count(__A      )
 lowercase       : dict[int, list[str]]						={
     freq: [] for letter, freq in letter_to_freq.items()
 }
 for letter in LETTERS:
  freq_to_letter[letter_to_freq[letter]].append(__A      )

 lowercase       : dict[int, str]						={}

 for freq in freq_to_letter:
  freq_to_letter[freq].sort(key=ETAOIN.find       ,   reverse=__A      )
  lowercase       : Optional[int]						=''''''.join(freq_to_letter[freq]      )

 lowercase       : str						=list(freq_to_letter_str.items()      )
 freq_pairs.sort(key=__A       ,   reverse=__A      )

 lowercase       : list[str]						=[freq_pair[1] for freq_pair in freq_pairs]

 return "".join(__A      )


def 				lowercase_					(     __A			:							str      )							->   int:



 """simple docstring"""




 lowercase       : Optional[Any]						=get_frequency_order(__A      )
 lowercase       : Union[str, Any]						=0
 for common_letter in ETAOIN[:6]:
  if common_letter in freq_order[:6]:
   match_score += 1

 for uncommon_letter in ETAOIN[-6:]:
  if uncommon_letter in freq_order[-6:]:
   match_score += 1

 return match_score


if __name__ == "__main__":
      import doctest

      doctest.testmod()



