





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


lowercase_		:				Any				=						logging.get_logger(__name__)

lowercase_		:				List[Any]				=						{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase_		:				str				=						{
    '''vocab_file''': {
        '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt''',
        '''distilbert-base-uncased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt'''
        ),
        '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt''',
        '''distilbert-base-cased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt'''
        ),
        '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt''',
        '''distilbert-base-multilingual-cased''': (
            '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json''',
        '''distilbert-base-uncased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json'''
        ),
        '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json''',
        '''distilbert-base-cased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json'''
        ),
        '''distilbert-base-german-cased''': (
            '''https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json'''
        ),
        '''distilbert-base-multilingual-cased''': (
            '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json'''
        ),
    },
}

lowercase_		:				List[str]				=						{
    '''distilbert-base-uncased''': 512,
    '''distilbert-base-uncased-distilled-squad''': 512,
    '''distilbert-base-cased''': 512,
    '''distilbert-base-cased-distilled-squad''': 512,
    '''distilbert-base-german-cased''': 512,
    '''distilbert-base-multilingual-cased''': 512,
}


lowercase_		:				List[str]				=						{
    '''distilbert-base-uncased''': {'''do_lower_case''': True},
    '''distilbert-base-uncased-distilled-squad''': {'''do_lower_case''': True},
    '''distilbert-base-cased''': {'''do_lower_case''': False},
    '''distilbert-base-cased-distilled-squad''': {'''do_lower_case''': False},
    '''distilbert-base-german-cased''': {'''do_lower_case''': False},
    '''distilbert-base-multilingual-cased''': {'''do_lower_case''': False},
}


class 			lowercase				(							a_     ):



      """simple docstring"""

      _UpperCamelCase  :	Dict								=	VOCAB_FILES_NAMES
      _UpperCamelCase  :	int								=	PRETRAINED_VOCAB_FILES_MAP
      _UpperCamelCase  :	Dict								=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _UpperCamelCase  :	List[str]								=	PRETRAINED_INIT_CONFIGURATION
      _UpperCamelCase  :	Union[str, Any]								=	["input_ids", "attention_mask"]
      _UpperCamelCase  :	Any								=	DistilBertTokenizer







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





          '''simple docstring'''







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

          _snake_case :			Union[str, Any]  						=   json.loads(self.backend_tokenizer.normalizer.__getstate__()					)
          if (
              normalizer_state.get('lowercase' ,				lowerCamelCase_					) != do_lower_case
              or normalizer_state.get('strip_accents' ,				lowerCamelCase_					) != strip_accents
              or normalizer_state.get('handle_chinese_chars' ,				lowerCamelCase_					) != tokenize_chinese_chars
          ):
              _snake_case :			Tuple  						=   getattr(lowerCamelCase_ ,				normalizer_state.pop('type'					)					)
              _snake_case :			Optional[Any]  						=   do_lower_case
              _snake_case :			str  						=   strip_accents
              _snake_case :			List[str]  						=   tokenize_chinese_chars
              _snake_case :			List[Any]  						=   normalizer_class(**lowerCamelCase_					)

          _snake_case :			List[Any]  						=   do_lower_case







      def 		__UpperCAmelCase       (    self			:		int ,				lowerCamelCase_			:		Tuple ,				lowerCamelCase_			:		Optional[int]=None					):





          '''simple docstring'''







          _snake_case :			Dict  						=   [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 		__UpperCAmelCase       (    self			:		List[str] ,				lowerCamelCase_			:		List[int] ,				lowerCamelCase_			:		Optional[List[int]] = None					):





          '''simple docstring'''







          _snake_case :			Union[str, Any]  						=   [self.sep_token_id]
          _snake_case :			Dict  						=   [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 		__UpperCAmelCase       (    self			:		Optional[Any] ,				lowerCamelCase_			:		str ,				lowerCamelCase_			:		Optional[str] = None					):





          '''simple docstring'''







          _snake_case :			Dict  						=   self._tokenizer.model.save(lowerCamelCase_ ,				name=lowerCamelCase_					)
          return tuple(lowerCamelCase_					)













from math import factorial

def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				if successes > trials:
								raise ValueError('successes must be lower or equal to trials' )
				if trials < 0 or successes < 0:
								raise ValueError('the function is defined for non-negative integers' )
				if not isinstance(__lowerCAmelCase	,			__lowerCAmelCase ) or not isinstance(__lowerCAmelCase	,			__lowerCAmelCase ):
								raise ValueError('the function is defined for non-negative integers' )
				if not 0 < prob < 1:
								raise ValueError('prob has to be in range of 1 - 0' )
				_snake_case :			Optional[int]  						=   (prob**successes) * ((1 - prob) ** (trials - successes))
				# Calculate the binomial coefficient: n! / k!(n-k)!
				_snake_case :			List[Any]  						=   float(factorial(__lowerCAmelCase ) )
				coefficient /= factorial(__lowerCAmelCase ) * factorial(trials - successes )
				return probability * coefficient


if __name__ == "__main__":
		from doctest import testmod

		testmod()
		print('''Probability of 2 successes out of 4 trails''')
		print('''with probability of 0.75 is:''', end=''' ''')
		print(binomial_distribution(2, 4, 0.75))






