
"""simple docstring"""


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer


_lowercase							      = logging.get_logger(__name__)

_lowercase							      = {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

_lowercase							      = {
    '''vocab_file''': {
        '''squeezebert/squeezebert-uncased''': (
            '''https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/vocab.txt'''
        ),
        '''squeezebert/squeezebert-mnli''': '''https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/vocab.txt''',
        '''squeezebert/squeezebert-mnli-headless''': (
            '''https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''squeezebert/squeezebert-uncased''': (
            '''https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/tokenizer.json'''
        ),
        '''squeezebert/squeezebert-mnli''': (
            '''https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/tokenizer.json'''
        ),
        '''squeezebert/squeezebert-mnli-headless''': (
            '''https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/tokenizer.json'''
        ),
    },
}

_lowercase							      = {
    '''squeezebert/squeezebert-uncased''': 5_12,
    '''squeezebert/squeezebert-mnli''': 5_12,
    '''squeezebert/squeezebert-mnli-headless''': 5_12,
}


_lowercase							      = {
    '''squeezebert/squeezebert-uncased''': {'''do_lower_case''': True},
    '''squeezebert/squeezebert-mnli''': {'''do_lower_case''': True},
    '''squeezebert/squeezebert-mnli-headless''': {'''do_lower_case''': True},
}







class  lowerCAmelCase_ (					_lowercase			):



						'''simple docstring'''


						_lowerCamelCase:			Dict					=			VOCAB_FILES_NAMES
						_lowerCamelCase:			Dict					=			PRETRAINED_VOCAB_FILES_MAP
						_lowerCamelCase:			List[Any]					=			PRETRAINED_INIT_CONFIGURATION
						_lowerCamelCase:			Tuple					=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_lowerCamelCase:			List[str]					=			SqueezeBertTokenizer


						def __init__(       self   :					List[Any]     ,A_   :					Optional[Any]=None     ,A_   :					Any=None     ,A_   :					Optional[Any]=True     ,A_   :					str="[UNK]"     ,A_   :					Optional[int]="[SEP]"     ,A_   :					Dict="[PAD]"     ,A_   :					Tuple="[CLS]"     ,A_   :					Dict="[MASK]"     ,A_   :					Tuple=True     ,A_   :					Tuple=None     ,**A_   :					int     ,)   ->      Union[str, Any]:
							super().__init__(
							    A_     ,tokenizer_file=A_     ,do_lower_case=A_     ,unk_token=A_     ,sep_token=A_     ,pad_token=A_     ,cls_token=A_     ,mask_token=A_     ,tokenize_chinese_chars=A_     ,strip_accents=A_     ,**A_     ,)

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

							A        =      do_lower_case


						def   _SCREAMING_SNAKE_CASE					(       self   :					List[Any]     ,A_   :					List[str]     ,A_   :					Optional[int]=None					)   ->      str:
							A        =      [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   _SCREAMING_SNAKE_CASE					(       self   :					str     ,A_   :					List[int]     ,A_   :					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   _SCREAMING_SNAKE_CASE					(       self   :					int     ,A_   :					str     ,A_   :					Optional[str] = None					)   ->      Tuple[str]:
							A        =      self._tokenizer.model.save(A_     ,name=A_					)
							return tuple(A_					)







def 						_a    (      a :int )							->			list:

 # bit count represents no. of bits in the gray code
 if bit_count < 0:
  raise ValueError('''The given input must be positive''' )

 # get the generated string sequence
 a		  =      gray_code_sequence_string(a )
 #
 # convert them to integers
 for i in range(len(a ) ):
  a		  =      int(sequence[i]	,							2 )

 return sequence
def 						_a    (      a :int )							->			list:

 # The approach is a recursive one
 # Base case achieved when either n = 0 or n=1
 if bit_count == 0:
  return ["0"]

 if bit_count == 1:
  return ["0", "1"]

 a		  =      1 << bit_count  # defines the length of the sequence
 # 1<< n is equivalent to 2^n

 # recursive answer will generate answer for n-1 bits
 a		  =      gray_code_sequence_string(bit_count - 1 )

 a		  =      []

 # append 0 to first half of the smaller sequence generated
 for i in range(seq_len // 2 ):
  a		  =      '''0''' + smaller_sequence[i]
  sequence.append(a )

 # append 1 to second half ... start from the end of the list
 for i in reversed(range(seq_len // 2 ) ):
  a		  =      '''1''' + smaller_sequence[i]
  sequence.append(a )

 return sequence


if __name__ == "__main__":
     import doctest

     doctest.testmod()


