






"""simple docstring"""


import torch

from transformers import AutoTokenizer


class    snake_case						(				_lowerCAmelCase		):


   '''simple docstring'''

   def __init__(      self					:	Dict,			_lowerCamelCase					:	Optional[int]    ):

     '''simple docstring'''
     __A		     =					AutoTokenizer.from_pretrained(_lowerCamelCase    )


   def 							_SCREAMING_SNAKE_CASE							(      self					:	str,			_lowerCamelCase					:	Optional[Any]    ):

     '''simple docstring'''

     if isinstance(_lowerCamelCase,			_lowerCamelCase    ) and all(isinstance(_x,			_lowerCamelCase    ) for _x in x    ):
       __A		     =					None
       for l in x:
         __A		     =					self.tokenizer(
             _lowerCamelCase,			padding='''max_length''',			max_length=3_84,			truncation=_lowerCamelCase,			return_tensors='''pt''',			)
         __A		     =					torch.tensor([len(_lowerCamelCase    )]    )
         if d is not None:
           for k in d.keys():
             __A		     =					torch.cat((d[k], t[k]),			0    )
         else:
           __A		     =					t

       __A		     =					torch.tensor(self.tokenizer.convert_tokens_to_ids('''[E]'''    )    )
       __A		     =					torch.tensor(self.tokenizer.convert_tokens_to_ids('''[/E]'''    )    )

     elif isinstance(_lowerCamelCase,			_lowerCamelCase    ) and all(isinstance(_x,			_lowerCamelCase    ) for _x in x    ):
       __A		     =					self.tokenizer(
           _lowerCamelCase,			padding='''max_length''',			max_length=3_84,			truncation=_lowerCamelCase,			return_tensors='''pt''',			)

     else:
       raise Exception(
           '''Type of parameter x was not recognized! Only `list of strings` for query or `list of lists of'''
           ''' strings` for supports are supported.'''    )

     return d






   def 							_SCREAMING_SNAKE_CASE							(      self					:	int,			_lowerCamelCase					:	Union[str, Any],			_lowerCamelCase					:	List[str],			_lowerCamelCase					:	str,			_lowerCamelCase					:	Optional[int],			_lowerCamelCase					:	Any=0.70    ):

     '''simple docstring'''
     __A		     =					[]
     for idx in range(len(W_query['''input_ids''']    )    ):
       __A		     =					__A		     =					range(p_start.shape[1]    )

       __A		     =					[]
       for start_id in start_indexes:
         for end_id in end_indexes:
           if start_id < end_id:
             output.append(
                 (
                     start_id,
                     end_id,
                     p_start[idx][start_id].item(),
                     p_end[idx][end_id].item(),
                 )    )

       output.sort(key=lambda _lowerCamelCase    : (tup[2] * tup[3]),			reverse=_lowerCamelCase    )
       __A		     =					[]
       for k in range(len(_lowerCamelCase    )    ):
         if output[k][2] * output[k][3] >= thresh:
           __A     ,       __A		     =					output[k][0], output[k][1]
           __A		     =					self.tokenizer.decode(W_query['''input_ids'''][idx][c_start_pos:c_end_pos]    )
           temp.append((decoded, output[k][2] * output[k][3])    )

       final_outputs.append(_lowerCamelCase    )

     return final_outputs










"""simple docstring"""
import math






def 				__lowerCAmelCase					(					__lowerCAmelCase			:		Tuple						)    ->       Any:
 _UpperCamelCase      :	str					      =  0
 if n % 2 == 0:
  count += 1
  while n % 2 == 0:
   _UpperCamelCase      :	List[Any]					      =  int(n / 2						)
    # the n input value must be odd so that
    # we can skip one element (ie i += 2)

 _UpperCamelCase      :	Tuple					      =  3

 while i <= int(math.sqrt(__lowerCAmelCase						)						):
  if n % i == 0:
   count += 1
   while n % i == 0:
    _UpperCamelCase      :	Any					      =  int(n / i						)
  _UpperCamelCase      :	Optional[Any]					      =  i + 2

 # this condition checks the prime
 # number n is greater than 2

 if n > 2:
  count += 1
 return count


if __name__ == "__main__":
    _SCREAMING_SNAKE_CASE						 =     5_1_2_4_2_1_8_3
    print(f'The number of distinct prime factors is/are {exact_prime_factor_count(n)}')
    print(f'The value of log(log(n)) is {math.log(math.log(n)):.4f}')



