




import copy
import random

from transformers import CLIPTokenizer







class 		lowercase_   (			A       ):


   """simple docstring"""

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

      """simple docstring"""
      super().__init__(*__lowerCamelCase  ,				**__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				{}



   def 							lowerCAmelCase_      (   self :     List[str]  ,				__lowerCamelCase :     Dict  ,				*__lowerCamelCase :     List[Any]  ,				**__lowerCamelCase :     List[str]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				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 							lowerCAmelCase_      (   self :     List[Any]  ,				__lowerCamelCase :     Union[str, Any]  ,				*__lowerCamelCase :     Optional[Any]  ,				__lowerCamelCase :     List[str]=1  ,				**__lowerCamelCase :     Any   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				[]
      if num_vec_per_token == 1:
         self.try_adding_tokens(__lowerCamelCase  ,				*__lowerCamelCase  ,				**__lowerCamelCase   )
         output.append(__lowerCamelCase   )
      else:
         _SCREAMING_SNAKE_CASE	=				[]
         for i in range(__lowerCamelCase   ):
            _SCREAMING_SNAKE_CASE	=				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"""   )
      _SCREAMING_SNAKE_CASE	=				output



   def 							lowerCAmelCase_      (   self :     List[str]  ,				__lowerCamelCase :     List[Any]  ,				__lowerCamelCase :     List[Any]=False  ,				__lowerCamelCase :     List[str]=1.0   ):

      """simple docstring"""
      if isinstance(__lowerCamelCase  ,				__lowerCamelCase   ):
         _SCREAMING_SNAKE_CASE	=				[]
         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:
            _SCREAMING_SNAKE_CASE	=				self.token_map[placeholder_token]
            _SCREAMING_SNAKE_CASE	=				tokens[: 1 + int(len(__lowerCamelCase   ) * prop_tokens_to_load   )]
            if vector_shuffle:
               _SCREAMING_SNAKE_CASE	=				copy.copy(__lowerCamelCase   )
               random.shuffle(__lowerCamelCase   )
            _SCREAMING_SNAKE_CASE	=				text.replace(__lowerCamelCase  ,				" ".join(__lowerCamelCase   )   )
      return text



   def __call__(   self :     str  ,				__lowerCamelCase :     List[Any]  ,				*__lowerCamelCase :     List[str]  ,				__lowerCamelCase :     List[str]=False  ,				__lowerCamelCase :     Optional[Any]=1.0  ,				**__lowerCamelCase :     Any   ):

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



   def 							lowerCAmelCase_      (   self :     Optional[int]  ,				__lowerCamelCase :     Dict  ,				*__lowerCamelCase :     Any  ,				__lowerCamelCase :     Union[str, Any]=False  ,				__lowerCamelCase :     Optional[Any]=1.0  ,				**__lowerCamelCase :     Dict   ):

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







'''simple docstring'''



import random
def 			SCREAMING_SNAKE_CASE_			(							__A    :			int	,					__A    :			float	,					__A    :			bool = False  )			->			dict:
   _SCREAMING_SNAKE_CASE	=				{i: [] for i in range(__A  )}

   # if probability is greater or equal than 1, then generate a complete graph
   if probability >= 1:
      return complete_graph(__A  )
   # if probability is lower or equal than 0, then return a graph without edges
   if probability <= 0:
      return graph

   # for each couple of nodes, add an edge from u to v
   # if the number randomly generated is greater than probability probability
   for i in range(__A  ):
      for j in range(i + 1	,					__A  ):
         if random.random() < probability:
            graph[i].append(__A  )
            if not directed:
               # if the graph is undirected, add an edge in from j to i, either
               graph[j].append(__A  )
   return graph
def 			SCREAMING_SNAKE_CASE_			(							__A    :			int  )			->			dict:
   return {
       i: [j for j in range(__A  ) if i != j] for i in range(__A  )
   }


if __name__ == "__main__":
 import doctest

 doctest.testmod()

