





"""simple docstring"""



import copy
import random

from transformers import CLIPTokenizer






class 		__snake_case					(		SCREAMING_SNAKE_CASE__     ):





 """simple docstring"""


 def __init__(    self					,						*__lowerCamelCase					,						**__lowerCamelCase  ):



     '''simple docstring'''




     super().__init__(*__lowerCamelCase					,						**__lowerCamelCase  )
     __A    :						Dict						 =     {}

 def 					UpperCamelCase__(    self					,						__lowerCamelCase					,						*__lowerCamelCase					,						**__lowerCamelCase  ):



     '''simple docstring'''




     __A    :						str						 =     super().add_tokens(__lowerCamelCase					,						*__lowerCamelCase					,						**__lowerCamelCase  )
     if num_added_tokens == 0:
         raise ValueError(
             F"""The tokenizer already contains the token {placeholder_token}. Please pass a different"""
             ''' `placeholder_token` that is not already in the tokenizer.'''  )

 def 					UpperCamelCase__(    self					,						__lowerCamelCase					,						*__lowerCamelCase					,						__lowerCamelCase=1					,						**__lowerCamelCase  ):



     '''simple docstring'''




     __A    :						Tuple						 =     []
     if num_vec_per_token == 1:
         self.try_adding_tokens(__lowerCamelCase					,						*__lowerCamelCase					,						**__lowerCamelCase  )
         output.append(__lowerCamelCase  )
     else:
         __A    :						Dict						 =     []
         for i in range(__lowerCamelCase  ):
             __A    :						Tuple						 =     placeholder_token + F"""_{i}"""
             self.try_adding_tokens(__lowerCamelCase					,						*__lowerCamelCase					,						**__lowerCamelCase  )
             output.append(__lowerCamelCase  )
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
     for token in self.token_map:
         if token in placeholder_token:
             raise ValueError(
                 F"""The tokenizer already has placeholder token {token} that can get confused with"""
                 F""" {placeholder_token}keep placeholder tokens independent"""  )
     __A    :						Optional[int]						 =     output

 def 					UpperCamelCase__(    self					,						__lowerCamelCase					,						__lowerCamelCase=False					,						__lowerCamelCase=1.0  ):



     '''simple docstring'''




     if isinstance(__lowerCamelCase					,						__lowerCamelCase  ):
         __A    :						Tuple						 =     []
         for i in range(len(__lowerCamelCase  )  ):
             output.append(self.replace_placeholder_tokens_in_text(text[i]					,						vector_shuffle=__lowerCamelCase  )  )
         return output
     for placeholder_token in self.token_map:
         if placeholder_token in text:
             __A    :						List[str]						 =     self.token_map[placeholder_token]
             __A    :						int						 =     tokens[: 1 + int(len(__lowerCamelCase  ) * prop_tokens_to_load  )]
             if vector_shuffle:
                 __A    :						Tuple						 =     copy.copy(__lowerCamelCase  )
                 random.shuffle(__lowerCamelCase  )
             __A    :						List[Any]						 =     text.replace(__lowerCamelCase					,						''' '''.join(__lowerCamelCase  )  )
     return text

 def __call__(    self					,						__lowerCamelCase					,						*__lowerCamelCase					,						__lowerCamelCase=False					,						__lowerCamelCase=1.0					,						**__lowerCamelCase  ):



     '''simple docstring'''




     return super().__call__(
         self.replace_placeholder_tokens_in_text(
             __lowerCamelCase					,						vector_shuffle=__lowerCamelCase					,						prop_tokens_to_load=__lowerCamelCase  )					,						*__lowerCamelCase					,						**__lowerCamelCase					,						)







 def 					UpperCamelCase__(    self					,						__lowerCamelCase					,						*__lowerCamelCase					,						__lowerCamelCase=False					,						__lowerCamelCase=1.0					,						**__lowerCamelCase  ):



     '''simple docstring'''




     return super().encode(
         self.replace_placeholder_tokens_in_text(
             __lowerCamelCase					,						vector_shuffle=__lowerCamelCase					,						prop_tokens_to_load=__lowerCamelCase  )					,						*__lowerCamelCase					,						**__lowerCamelCase					,						)











"""simple docstring"""



def 		__lowercase     (   snake_case_  :  int						)   ->int:



    '''simple docstring'''







    assert (
        isinstance(snake_case_				,snake_case_						) and number_of_steps > 0
    ), F"""number_of_steps needs to be positive integer, your input {number_of_steps}"""
    if number_of_steps == 1:
        return 1
    __A ,       __A    :						List[Any]						 =     1, 1
    for _ in range(number_of_steps - 1						):
        __A ,       __A    :						List[str]						 =     current + previous, current
    return current


if __name__ == "__main__":
       import doctest

       doctest.testmod()




