





import json
import os
from typing import Optional, Tuple

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


_UpperCAmelCase				:       List[str]	   =				logging.get_logger(__name__)

_UpperCAmelCase				:       Tuple	   =				{"""vocab_file""": """vocab.json"""}

_UpperCAmelCase				:       List[str]	   =				{
    """vocab_file""": {
        """mgp-str""": """https://huggingface.co/alibaba-damo/mgp-str-base/blob/main/vocab.json""",
    }
}

_UpperCAmelCase				:       str	   =				{"""mgp-str""": 27}

class    lowerCAmelCase							(					__UpperCamelCase			):
 UpperCAmelCase__													=		VOCAB_FILES_NAMES
 UpperCAmelCase__													=		PRETRAINED_VOCAB_FILES_MAP
 UpperCAmelCase__													=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 def __init__(      self  :      List[Any]			,     UpperCAmelCase  :      List[Any]			,     UpperCAmelCase  :      Optional[int]="[GO]"			,     UpperCAmelCase  :      int="[GO]"			,     UpperCAmelCase  :      List[Any]="[s]"			,     UpperCAmelCase  :      str="[GO]"			,     **UpperCAmelCase  :      str	)			->	List[str]:
     super().__init__(
         unk_token=UpperCAmelCase			,     bos_token=UpperCAmelCase			,     eos_token=UpperCAmelCase			,     pad_token=UpperCAmelCase			,     **UpperCAmelCase			,     )

     with open(UpperCAmelCase			,     encoding='utf-8'	) as vocab_handle:
         lowerCamelCase__    :      List[Any]					 =		json.load(UpperCAmelCase	)
     lowerCamelCase__    :      Optional[int]					 =		{v: k for k, v in self.vocab.items()}
 @property
 def      A_	(      self  :      List[str]	)			->	Tuple:
     return len(self.vocab	)
 def      A_	(      self  :      Union[str, Any]	)			->	Optional[int]:
     return dict(self.vocab			,     **self.added_tokens_encoder	)
 def      A_	(      self  :      Tuple			,     UpperCAmelCase  :      Union[str, Any]	)			->	Dict:
     lowerCamelCase__    :      Dict					 =		[]
     for s in text:
         char_tokens.extend(UpperCAmelCase	)
     return char_tokens
 def      A_	(      self  :      List[Any]			,     UpperCAmelCase  :      Union[str, Any]	)			->	Union[str, Any]:
     return self.vocab.get(UpperCAmelCase			,     self.vocab.get(self.unk_token	)	)
 def      A_	(      self  :      str			,     UpperCAmelCase  :      Dict	)			->	Tuple:
     return self.decoder.get(UpperCAmelCase	)







 def      A_	(      self  :      int			,     UpperCAmelCase  :      str			,     UpperCAmelCase  :      Optional[str] = None	)			->	Tuple[str]:
     if not os.path.isdir(UpperCAmelCase	):
         logger.error('Vocabulary path ({}) should be a directory'.format(UpperCAmelCase	)	)
         return
     lowerCamelCase__    :      str					 =		os.path.join(
         UpperCAmelCase			,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)

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

     return (vocab_file,)










from math import factorial
def        lowercase_							(A : int		,					A : int		,					A : float      ):
       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(A		,					A      ) or not isinstance(A		,					A      ):
              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__							:	List[Any]   	=	(prob**successes) * ((1 - prob) ** (trials - successes))
       # Calculate the binomial coefficient: n! / k!(n-k)!
       snake_case__							:	List[str]   	=	float(factorial(A      )      )
       coefficient /= factorial(A      ) * 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))






