






"""simple docstring"""


class 						snake_case  :





    def __init__(							self     : Optional[int]      ):


      '''simple docstring'''




      _A					:      dict[str, TrieNode]    =       {}  # Mapping from char to TrieNode
      _A					:      str    =       False





    def     lowerCamelCase__				(							self     : Tuple    ,		A     : list[str]      ):


      '''simple docstring'''




      for word in words:
        self.insert(A      )





    def     lowerCamelCase__				(							self     : Dict    ,		A     : str      ):


      '''simple docstring'''




      _A					:      List[str]    =       self
      for char in word:
        if char not in curr.nodes:
          _A					:      Dict    =       TrieNode()
        _A					:      Any    =       curr.nodes[char]
      _A					:      List[str]    =       True





    def     lowerCamelCase__				(							self     : str    ,		A     : str      ):


      '''simple docstring'''




      _A					:      Tuple    =       self
      for char in word:
        if char not in curr.nodes:
          return False
        _A					:      Optional[Any]    =       curr.nodes[char]
      return curr.is_leaf





    def     lowerCamelCase__				(							self     : int    ,		A     : str      ):


      '''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
          _A					:      int    =       False
          return len(curr.nodes      ) == 0
        _A					:      Tuple    =       word[index]
        _A					:      Dict    =       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
        _A					:      str    =       _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       snake_case  (A_				:TrieNode     ,      A_				:str				):







  '''simple docstring'''

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

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




def       snake_case  ():







  '''simple docstring'''

  _A					:      Dict    =       'banana bananas bandana band apple all beast'.split()
  _A					:      Optional[Any]    =       TrieNode()
  root.insert_many(A_				)
  # print_words(root, "")
  assert all(root.find(A_				) 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       snake_case  (A_				:str     ,      A_				:bool				):







  '''simple docstring'''

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




def       snake_case  ():







  '''simple docstring'''

  assert test_trie()




def       snake_case  ():







  '''simple docstring'''

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


if __name__ == "__main__":
   main()












"""simple docstring"""


import os
import sys

_UpperCamelCase    :   str   			=						os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


_UpperCamelCase    :   int   			=						[
    'torch',
    'numpy',
    'tokenizers',
    'filelock',
    'requests',
    'tqdm',
    'regex',
    'sentencepiece',
    'sacremoses',
    'importlib_metadata',
    'huggingface_hub',
]




@add_start_docstrings(AutoConfig.__doc__				)
def       snake_case  (*A_				:Optional[int]     ,      **A_				:int				):







  '''simple docstring'''

  return AutoConfig.from_pretrained(*A_     ,      **A_				)




@add_start_docstrings(AutoTokenizer.__doc__				)
def       snake_case  (*A_				:Optional[int]     ,      **A_				:List[Any]				):







  '''simple docstring'''

  return AutoTokenizer.from_pretrained(*A_     ,      **A_				)




@add_start_docstrings(AutoModel.__doc__				)
def       snake_case  (*A_				:Optional[Any]     ,      **A_				:Tuple				):







  '''simple docstring'''

  return AutoModel.from_pretrained(*A_     ,      **A_				)




@add_start_docstrings(AutoModelForCausalLM.__doc__				)
def       snake_case  (*A_				:str     ,      **A_				:Optional[int]				):







  '''simple docstring'''

  return AutoModelForCausalLM.from_pretrained(*A_     ,      **A_				)




@add_start_docstrings(AutoModelForMaskedLM.__doc__				)
def       snake_case  (*A_				:Optional[Any]     ,      **A_				:Dict				):







  '''simple docstring'''

  return AutoModelForMaskedLM.from_pretrained(*A_     ,      **A_				)




@add_start_docstrings(AutoModelForSequenceClassification.__doc__				)
def       snake_case  (*A_				:Dict     ,      **A_				:str				):







  '''simple docstring'''

  return AutoModelForSequenceClassification.from_pretrained(*A_     ,      **A_				)






@add_start_docstrings(AutoModelForQuestionAnswering.__doc__				)
def       snake_case  (*A_				:Dict     ,      **A_				:List[Any]				):







  '''simple docstring'''

  return AutoModelForQuestionAnswering.from_pretrained(*A_     ,      **A_				)




