





class     __lowerCAmelCase	:







       def __init__(   self		,				lowerCAmelCase__ = ""		,				lowerCAmelCase__ = False							)       ->						None:



         '''simple docstring'''




         a__     : dict[str, RadixNode]  ={}

         # A node will be a leaf if the tree contains its word
         a__     : Optional[int]  =is_leaf

         a__     : str  =prefix







       def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						tuple[str, str, str]:



         '''simple docstring'''




         a__     : Optional[int]  =0
         for q, w in zip(self.prefix		,				snake_case__							):
           if q != w:
             break

           x += 1

         return self.prefix[:x], self.prefix[x:], word[x:]







       def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						None:



         '''simple docstring'''




         for word in words:
           self.insert(snake_case__							)







       def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						None:



         '''simple docstring'''




         if self.prefix == word:
           a__     : List[Any]  =True

         # Case 2: The node has no edges that have a prefix to the word
         # Solution: We create an edge from the current node to a new one
         # containing the word
         elif word[0] not in self.nodes:
           a__     : Tuple  =RadixNode(prefix=snake_case__		,				is_leaf=snake_case__							)

         else:
           a__     : str  =self.nodes[word[0]]
           a__     : Optional[Any]  =incoming_node.match(
               snake_case__							)

           # Case 3: The node prefix is equal to the matching
           # Solution: We insert remaining word on the next node
           if remaining_prefix == "":
             self.nodes[matching_string[0]].insert(snake_case__							)

           # Case 4: The word is greater equal to the matching
           # Solution: Create a node in between both nodes, change
           # prefixes and add the new node for the remaining word
           else:
             a__     : Optional[Any]  =remaining_prefix

             a__     : Optional[Any]  =self.nodes[matching_string[0]]
             a__     : str  =RadixNode(snake_case__		,				snake_case__							)
             a__     : List[str]  =aux_node

             if remaining_word == "":
               a__     : int  =True
             else:
               self.nodes[matching_string[0]].insert(snake_case__							)







       def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						bool:



         '''simple docstring'''




         a__     : Optional[int]  =self.nodes.get(word[0]		,				snake_case__							)
         if not incoming_node:
           return False
         else:
           a__     : Dict  =incoming_node.match(
               snake_case__							)
           # If there is remaining prefix, the word can't be on the tree
           if remaining_prefix != "":
             return False
           # This applies when the word and the prefix are equal
           elif remaining_word == "":
             return incoming_node.is_leaf
           # We have word remaining so we check the next node
           else:
             return incoming_node.find(snake_case__							)







       def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						bool:



         '''simple docstring'''




         a__     : Tuple  =self.nodes.get(word[0]		,				snake_case__							)
         if not incoming_node:
           return False
         else:
           a__     : str  =incoming_node.match(
               snake_case__							)
           # If there is remaining prefix, the word can't be on the tree
           if remaining_prefix != "":
             return False
           # We have word remaining so we check the next node
           elif remaining_word != "":
             return incoming_node.delete(snake_case__							)
           else:
             # If it is not a leaf, we don't have to delete
             if not incoming_node.is_leaf:
               return False
             else:
               # We delete the nodes if no edges go from it
               if len(incoming_node.nodes							) == 0:
                 del self.nodes[word[0]]
                 # We merge the current node with its only child
                 if len(self.nodes							) == 1 and not self.is_leaf:
                   a__     : List[str]  =list(self.nodes.values()							)[0]
                   a__     : int  =merging_node.is_leaf
                   self.prefix += merging_node.prefix
                   a__     : Tuple  =merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
               elif len(incoming_node.nodes							) > 1:
                 a__     : Tuple  =False
               # If there is 1 edge, we merge it with its child
               else:
                 a__     : List[str]  =list(incoming_node.nodes.values()							)[0]
                 a__     : Any  =merging_node.is_leaf
                 incoming_node.prefix += merging_node.prefix
                 a__     : Any  =merging_node.nodes

               return True







       def        _lowercase  (   self		,				lowerCAmelCase__ = 0							)       ->						None:



         '''simple docstring'''




         if self.prefix != "":
           print("-" * height		,				self.prefix		,				"  (leaf)" if self.is_leaf else ""							)

         for value in self.nodes.values():
           value.print_tree(height + 1							)
def 					_A	(		):





  """simple docstring"""



  a__     : Tuple  ="banana bananas bandana band apple all beast".split()
  a__     : Union[str, Any]  =RadixNode()
  root.insert_many(__lowerCamelCase						)

  assert all(root.find(__lowerCamelCase						) for word in words						)
  assert not root.find("bandanas"						)
  assert not root.find("apps"						)
  root.delete("all"						)
  assert not root.find("all"						)
  root.delete("banana"						)
  assert not root.find("banana"						)
  assert root.find("bananas"						)

  return True
def 					_A	(		):





  """simple docstring"""



  assert test_trie()
def 					_A	(		):





  """simple docstring"""



  a__     : List[str]  =RadixNode()
  a__     : List[Any]  ="banana bananas bandanas bandana band apple all beast".split()
  root.insert_many(__lowerCamelCase						)

  print("Words:"	,	__lowerCamelCase						)
  print("Tree:"						)
  root.print_tree()


if __name__ == "__main__":
     main()













import warnings

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase     :     Dict							=	logging.get_logger(__name__)

UpperCAmelCase     :     Dict							=	{
    """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",
}







class     __lowerCAmelCase	(   UpperCamelCase__):
      _lowercase    : List[Any]            =      """mvp"""
      _lowercase    : Tuple            =      ["""past_key_values"""]
      _lowercase    : Dict            =      {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}







      def __init__(   self		,				lowerCAmelCase__=5_0_2_6_7		,				lowerCAmelCase__=1_0_2_4		,				lowerCAmelCase__=1_2		,				lowerCAmelCase__=4_0_9_6		,				lowerCAmelCase__=1_6		,				lowerCAmelCase__=1_2		,				lowerCAmelCase__=4_0_9_6		,				lowerCAmelCase__=1_6		,				lowerCAmelCase__=0.0		,				lowerCAmelCase__=0.0		,				lowerCAmelCase__="gelu"		,				lowerCAmelCase__=1_0_2_4		,				lowerCAmelCase__=0.1		,				lowerCAmelCase__=0.0		,				lowerCAmelCase__=0.0		,				lowerCAmelCase__=0.02		,				lowerCAmelCase__=0.0		,				lowerCAmelCase__=False		,				lowerCAmelCase__=True		,				lowerCAmelCase__=1		,				lowerCAmelCase__=0		,				lowerCAmelCase__=2		,				lowerCAmelCase__=True		,				lowerCAmelCase__=2		,				lowerCAmelCase__=2		,				lowerCAmelCase__=False		,				lowerCAmelCase__=1_0_0		,				lowerCAmelCase__=8_0_0		,				**lowerCAmelCase__		,				)       ->						str:



        '''simple docstring'''




        a__     : Dict  =vocab_size
        a__     : List[str]  =max_position_embeddings
        a__     : List[str]  =d_model
        a__     : Optional[Any]  =encoder_ffn_dim
        a__     : Dict  =encoder_layers
        a__     : List[str]  =encoder_attention_heads
        a__     : List[str]  =decoder_ffn_dim
        a__     : Tuple  =decoder_layers
        a__     : Tuple  =decoder_attention_heads
        a__     : Any  =dropout
        a__     : str  =attention_dropout
        a__     : str  =activation_dropout
        a__     : Optional[int]  =activation_function
        a__     : Union[str, Any]  =init_std
        a__     : Dict  =encoder_layerdrop
        a__     : List[str]  =decoder_layerdrop
        a__     : Union[str, Any]  =classifier_dropout
        a__     : Union[str, Any]  =use_cache
        a__     : Optional[Any]  =encoder_layers
        a__     : List[str]  =scale_embedding  # scale factor will be sqrt(d_model) if True
        a__     : int  =use_prompt
        a__     : Union[str, Any]  =prompt_length
        a__     : Dict  =prompt_mid_dim

        super().__init__(
            pad_token_id=lowerCAmelCase__		,				bos_token_id=lowerCAmelCase__		,				eos_token_id=lowerCAmelCase__		,				is_encoder_decoder=lowerCAmelCase__		,				decoder_start_token_id=lowerCAmelCase__		,				forced_eos_token_id=lowerCAmelCase__		,				**lowerCAmelCase__		,				)

        if self.forced_bos_token_id is None and kwargs.get("force_bos_token_to_be_generated"		,				lowerCAmelCase__							):
          a__     : Tuple  =self.bos_token_id
          warnings.warn(
              F'''Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '''
              "The config can simply be saved and uploaded again to be fixed."							)






