




class     A:



 '''simple docstring'''


 def __init__(							self   :    List[str]    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       {}  # Mapping from char to TrieNode
       lowerCamelCase_							=       False

 def 							a__					(							self   :    Union[str, Any]		,				A_   :    list[str]    )  ->      None:

       """simple docstring"""






       for word in words:
             self.insert(A_    )

 def 							a__					(							self   :    Any		,				A_   :    str    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       self
       for char in word:
             if char not in curr.nodes:
                   lowerCamelCase_							=       TrieNode()
             lowerCamelCase_							=       curr.nodes[char]
       lowerCamelCase_							=       True

 def 							a__					(							self   :    Dict		,				A_   :    str    )  ->      bool:

       """simple docstring"""






       lowerCamelCase_							=       self
       for char in word:
             if char not in curr.nodes:
                   return False
             lowerCamelCase_							=       curr.nodes[char]
       return curr.is_leaf





 def 							a__					(							self   :    List[str]		,				A_   :    str    )  ->      None:

       """simple docstring"""






       def _delete(A_   :    TrieNode		,				A_   :    str		,				A_   :    int    ) -> bool:
             if index == len(A_    ):
                   # If word does not exist
                   if not curr.is_leaf:
                         return False
                   lowerCamelCase_							=       False
                   return len(curr.nodes    ) == 0
             lowerCamelCase_							=       word[index]
             lowerCamelCase_							=       curr.nodes.get(A_    )
             # If char not in current trie node
             if not char_node:
                   return False
             # Flag to check if node can be deleted
             lowerCamelCase_							=       _delete(A_		,				A_		,				index + 1    )
             if delete_curr:
                   del curr.nodes[char]
                   return len(curr.nodes    ) == 0
             return delete_curr

       _delete(self		,				A_		,				0    )

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			Union[str, Any]      ,				lowercase      :			str	):


      '''simple docstring'''



      if node.is_leaf:
            print(_lowerCamelCase      ,				end=' '	)

      for key, value in node.nodes.items():
            print_words(_lowerCamelCase      ,				word + key	)

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      lowerCamelCase_							=       """banana bananas bandana band apple all beast""".split()
      lowerCamelCase_							=       TrieNode()
      root.insert_many(_lowerCamelCase	)
      # print_words(root, "")
      assert all(root.find(_lowerCamelCase	) for word in words	)
      assert root.find('banana'	)
      assert not root.find('bandanas'	)
      assert not root.find('apps'	)
      assert root.find('apple'	)
      assert root.find('all'	)
      root.delete('all'	)
      assert not root.find('all'	)
      root.delete('banana'	)
      assert not root.find('banana'	)
      assert root.find('bananas'	)
      return True

def      _SCREAMING_SNAKE_CASE     (				lowercase      :			int      ,				lowercase      :			str	):


      '''simple docstring'''



      print(str(_lowerCamelCase	)      ,				'works!' if passes else 'doesn\'t work :('	)

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      assert test_trie()

def      _SCREAMING_SNAKE_CASE     (				):


      '''simple docstring'''



      print_results('Testing trie functionality'      ,				test_trie()	)


if __name__ == "__main__":
 main()










'''simple docstring'''






import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding




class  _A (					__lowercase		):
		lowercase__:   Any				     =   ['''image_processor''', '''tokenizer''']
		lowercase__:   Any				     =   '''CLIPImageProcessor'''
		lowercase__:   Optional[Any]				     =   ('''CLIPTokenizer''', '''CLIPTokenizerFast''')

		def __init__(   self					:   int  ,      __magic_name__					:   Dict=None  ,      __magic_name__					:   Dict=None  ,      **__magic_name__					:   Union[str, Any]			)					->    Any:


					"""simple docstring"""

					__snake_case					:      Optional[Any]							      =     None
					if "feature_extractor" in kwargs:
								warnings.warn(
								    """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
								    """ instead."""  ,      __magic_name__  ,      )
								__snake_case					:      List[Any]							      =     kwargs.pop("""feature_extractor"""			)

					__snake_case					:      List[str]							      =     image_processor if image_processor is not None else feature_extractor
					if image_processor is None:
								raise ValueError("""You need to specify an `image_processor`."""			)
					if tokenizer is None:
								raise ValueError("""You need to specify a `tokenizer`."""			)

					super().__init__(__magic_name__  ,      __magic_name__			)

		def __call__(   self					:   int  ,      __magic_name__					:   List[str]=None  ,      __magic_name__					:   Tuple=None  ,      __magic_name__					:   Any=None  ,      **__magic_name__					:   Union[str, Any]			)					->    Optional[int]:


					"""simple docstring"""

					if text is None and images is None:
								raise ValueError("""You have to specify either text or images. Both cannot be none."""			)

					if text is not None:
								__snake_case					:      int							      =     self.tokenizer(__magic_name__  ,      return_tensors=__magic_name__  ,      **__magic_name__			)

					if images is not None:
								__snake_case					:      str							      =     self.image_processor(__magic_name__  ,      return_tensors=__magic_name__  ,      **__magic_name__			)

					if text is not None and images is not None:
								__snake_case					:      Union[str, Any]							      =     image_features.pixel_values
								return encoding
					elif text is not None:
								return encoding
					else:
								return BatchEncoding(data=dict(**__magic_name__			)  ,      tensor_type=__magic_name__			)

		def 	lowercase__     (   self					:   Optional[int]  ,      *__magic_name__					:   List[Any]  ,      **__magic_name__					:   Any			)					->    Optional[Any]:


					"""simple docstring"""

					return self.tokenizer.batch_decode(*__magic_name__  ,      **__magic_name__			)

		def 	lowercase__     (   self					:   List[str]  ,      *__magic_name__					:   Tuple  ,      **__magic_name__					:   List[Any]			)					->    int:


					"""simple docstring"""

					return self.tokenizer.decode(*__magic_name__  ,      **__magic_name__			)

		@property
		def 	lowercase__     (   self					:   List[Any]			)					->    Optional[Any]:


					"""simple docstring"""

					__snake_case					:      Dict							      =     self.tokenizer.model_input_names
					__snake_case					:      str							      =     self.image_processor.model_input_names
					return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)

		@property
		def 	lowercase__     (   self					:   int			)					->    List[str]:


					"""simple docstring"""

					warnings.warn(
					    """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""  ,      __magic_name__  ,      )
					return self.image_processor_class

		@property
		def 	lowercase__     (   self					:   Union[str, Any]			)					->    Dict:


					"""simple docstring"""

					warnings.warn(
					    """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""  ,      __magic_name__  ,      )
					return self.image_processor


