


"""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


UpperCAmelCase__  							=logging.get_logger(__name__)

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

UpperCAmelCase__  							={
    "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"
        ),
    },
}

UpperCAmelCase__  							={
    "squeezebert/squeezebert-uncased": 512,
    "squeezebert/squeezebert-mnli": 512,
    "squeezebert/squeezebert-mnli-headless": 512,
}


UpperCAmelCase__  							={
    "squeezebert/squeezebert-uncased": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli-headless": {"do_lower_case": True},
}





class    lowerCamelCase__						(		UpperCamelCase_    ):

      '''simple docstring'''





      a :     Dict											=		VOCAB_FILES_NAMES
      a :     Dict											=		PRETRAINED_VOCAB_FILES_MAP
      a :     List[str]											=		PRETRAINED_INIT_CONFIGURATION
      a :     Optional[int]											=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a :     List[Any]											=		SqueezeBertTokenizer
      def __init__(		self	:	str      ,       A_	:	List[str]=None      ,       A_	:	str=None      ,       A_	:	str=True      ,       A_	:	int="[UNK]"      ,       A_	:	Any="[SEP]"      ,       A_	:	Tuple="[PAD]"      ,       A_	:	Optional[Any]="[CLS]"      ,       A_	:	Dict="[MASK]"      ,       A_	:	Any=True      ,       A_	:	str=None      ,       **A_	:	str      ,       ):






       '''simple docstring'''


       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      ,       )

       __lowercase									=	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
       ):
        __lowercase									=	getattr(_a      ,       normalizer_state.pop("""type"""							)							)
        __lowercase									=	do_lower_case
        __lowercase									=	strip_accents
        __lowercase									=	tokenize_chinese_chars
        __lowercase									=	normalizer_class(**_a							)

       __lowercase									=	do_lower_case
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[Any]      ,       A_	:	Optional[int]      ,       A_	:	Optional[int]=None							):






       '''simple docstring'''


       __lowercase									=	[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	:	List[Any]      ,       A_	:	Any      ,       A_	:	int = None							):






       '''simple docstring'''


       __lowercase									=	[self.sep_token_id]
       __lowercase									=	[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	:	List[Any]      ,       A_	:	List[str]      ,       A_	:	Dict = None							):






       '''simple docstring'''


       __lowercase									=	self._tokenizer.model.save(_a      ,       name=_a							)
       return tuple(_a							)




"""simple docstring"""

# Algorithm for the pigeonhole sorting




def lowerCAmelCase_      (				UpperCamelCase__	: Dict ):






 """simple docstring"""







 __lowercase									=	min(UpperCamelCase__ )  # min() finds the minimum value
 __lowercase									=	max(UpperCamelCase__ )  # max() finds the maximum value

 __lowercase									=	max_val - min_val + 1  # size is difference of max and min values plus one

 # list of pigeonholes of size equal to the variable size
 __lowercase									=	[0] * size

 # Populate the pigeonholes.
 for x in a:
  assert isinstance(UpperCamelCase__				,   UpperCamelCase__ ), "integers only please"
  holes[x - min_val] += 1

 # Putting the elements back into the array in an order.
 __lowercase									=	0
 for count in range(UpperCamelCase__ ):
  while holes[count] > 0:
   holes[count] -= 1
   __lowercase									=	count + min_val
   i += 1


def lowerCAmelCase_      (				):






 """simple docstring"""







 __lowercase									=	[8, 3, 2, 7, 4, 6, 8]
 pigeonhole_sort(UpperCamelCase__ )
 print("""Sorted order is:"""				,   """ """.join(UpperCamelCase__ ) )


if __name__ == "__main__":
       main()
