
from __future__ import annotations


class 		__magic_name__ :





		def __init__(				self     :						Optional[int]    ,	lowerCamelCase__     :						List[Any]=None					):
							lowerCAmelCase		:       List[Any]							=  data
							lowerCAmelCase		:       Optional[Any]							=  None





		def __repr__(				self     :						Optional[Any]					):
							lowerCAmelCase		:       Optional[int]							=  []
							lowerCAmelCase		:       Optional[int]							=  self
							while temp:
												string_rep.append(f'''{temp.data}'''					)
												lowerCAmelCase		:       Any							=  temp.next
							return "->".join(lowerCamelCase__					)



def      UpperCAmelCase__				(							__magic_name__    :  list	):


					'''simple docstring'''

					if not elements_list:
										raise Exception('''The Elements List is empty'''	)

					lowerCAmelCase		:       Any							=  Node(elements_list[0]	)
					for i in range(1				,	len(SCREAMING_SNAKE_CASE__	)	):
										lowerCAmelCase		:       List[Any]							=  Node(elements_list[i]	)
										lowerCAmelCase		:       int							=  current.next
					return head
def      UpperCAmelCase__				(							__magic_name__    :  Node	):


					'''simple docstring'''

					if head_node is not None and isinstance(SCREAMING_SNAKE_CASE__				,	SCREAMING_SNAKE_CASE__	):
										print_reverse(head_node.next	)
										print(head_node.data	)
def      UpperCAmelCase__				(							):


					'''simple docstring'''

					from doctest import testmod

					testmod()

					lowerCAmelCase		:       List[str]							=  make_linked_list([14, 52, 14, 12, 43]	)
					print('''Linked List:'''	)
					print(SCREAMING_SNAKE_CASE__	)
					print('''Elements in Reverse:'''	)
					print_reverse(SCREAMING_SNAKE_CASE__	)


if __name__ == "__main__":
		main()








'''simple docstring'''



import copy
import random

from transformers import CLIPTokenizer
class 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):




      def __init__(	self			, *lowerCamelCase			, **lowerCamelCase   )				->Union[str, Any]:



         '''simple docstring'''
         super().__init__(*lowerCamelCase			, **lowerCamelCase   )
         __a					  =     {}




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )				->Dict:



         '''simple docstring'''
         __a					  =     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   )				->List[str]:



         '''simple docstring'''
         __a					  =     []
         if num_vec_per_token == 1:
            self.try_adding_tokens(lowerCamelCase			, *lowerCamelCase			, **lowerCamelCase   )
            output.append(lowerCamelCase   )
         else:
            __a					  =     []
            for i in range(lowerCamelCase   ):
               __a					  =     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					  =     output




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase=False			, lowerCamelCase=1.0   )				->int:



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




      def __call__(	self			, lowerCamelCase			, *lowerCamelCase			, lowerCamelCase=False			, lowerCamelCase=1.0			, **lowerCamelCase   )				->Optional[int]:



         '''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   )				->List[Any]:



         '''simple docstring'''
         return super().encode(
             self.replace_placeholder_tokens_in_text(
                 lowerCamelCase			, vector_shuffle=lowerCamelCase			, prop_tokens_to_load=lowerCamelCase   )			, *lowerCamelCase			, **lowerCamelCase			, )