




"""simple docstring"""




class   UpperCAmelCase_    :
		def __init__(						self       )						->       None:
					__lowercase			:  dict[str, TrieNode]								=       {}  # Mapping from char to TrieNode
					__lowercase			:  Dict								=       False
		def 	_lowerCamelCase							(						self				,						UpperCamelCase_       )						->       None:
					for word in words:
								self.insert(UpperCamelCase_       )
		def 	_lowerCamelCase							(						self				,						UpperCamelCase_       )						->       None:
					__lowercase			:  List[str]								=       self
					for char in word:
								if char not in curr.nodes:
											__lowercase			:  Optional[Any]								=       TrieNode()
								__lowercase			:  List[Any]								=       curr.nodes[char]
					__lowercase			:  List[str]								=       True
		def 	_lowerCamelCase							(						self				,						UpperCamelCase_       )						->       bool:
					__lowercase			:  List[str]								=       self
					for char in word:
								if char not in curr.nodes:
											return False
								__lowercase			:  Tuple								=       curr.nodes[char]
					return curr.is_leaf
		def 	_lowerCamelCase							(						self				,						UpperCamelCase_       )						->       None:

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

					_delete(self				,						UpperCamelCase_				,						0       )







def      __UpperCAmelCase     ( __UpperCamelCase	,				__UpperCamelCase	):
			if node.is_leaf:
						print(__UpperCamelCase	,				end=''' '''	)

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







def      __UpperCAmelCase     ( ):
			__lowercase			:  Optional[int]								=       '''banana bananas bandana band apple all beast'''.split()
			__lowercase			:  str								=       TrieNode()
			root.insert_many(__UpperCamelCase	)
			# print_words(root, "")
			assert all(root.find(__UpperCamelCase	) 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      __UpperCAmelCase     ( __UpperCamelCase	,				__UpperCamelCase	):
			print(str(__UpperCamelCase	)	,				'''works!''' if passes else '''doesn\'t work :('''	)







def      __UpperCAmelCase     ( ):
			assert test_trie()







def      __UpperCAmelCase     ( ):
			print_results('''Testing trie functionality'''	,				test_trie()	)


if __name__ == "__main__":
			main()











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


lowerCamelCase      :       Optional[int]    =						logging.get_logger(__name__)

lowerCamelCase      :       Optional[Any]    =						{
    '''google/pegasus-large''': '''https://huggingface.co/google/pegasus-large/resolve/main/config.json''',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}



class 				_UpperCamelCase      (a_      ):
      snake_case_	=				"""pegasus"""
      snake_case_	=				["""past_key_values"""]
      snake_case_	=				{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}


      def __init__(						self       ,    __UpperCamelCase=5_0_2_6_5       ,    __UpperCamelCase=1_0_2_4       ,    __UpperCamelCase=1_2       ,    __UpperCamelCase=4_0_9_6       ,    __UpperCamelCase=1_6       ,    __UpperCamelCase=1_2       ,    __UpperCamelCase=4_0_9_6       ,    __UpperCamelCase=1_6       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=True       ,    __UpperCamelCase=True       ,    __UpperCamelCase="gelu"       ,    __UpperCamelCase=1_0_2_4       ,    __UpperCamelCase=0.1       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=0.0_2       ,    __UpperCamelCase=0       ,    __UpperCamelCase=False       ,    __UpperCamelCase=0       ,    __UpperCamelCase=1       ,    __UpperCamelCase=1       ,    **__UpperCamelCase       ,    )->						Tuple:
           __lowerCAmelCase             =       vocab_size
           __lowerCAmelCase             =       max_position_embeddings
           __lowerCAmelCase             =       d_model
           __lowerCAmelCase             =       encoder_ffn_dim
           __lowerCAmelCase             =       encoder_layers
           __lowerCAmelCase             =       encoder_attention_heads
           __lowerCAmelCase             =       decoder_ffn_dim
           __lowerCAmelCase             =       decoder_layers
           __lowerCAmelCase             =       decoder_attention_heads
           __lowerCAmelCase             =       dropout
           __lowerCAmelCase             =       attention_dropout
           __lowerCAmelCase             =       activation_dropout
           __lowerCAmelCase             =       activation_function
           __lowerCAmelCase             =       init_std
           __lowerCAmelCase             =       encoder_layerdrop
           __lowerCAmelCase             =       decoder_layerdrop
           __lowerCAmelCase             =       use_cache
           __lowerCAmelCase             =       encoder_layers
           __lowerCAmelCase             =       scale_embedding  # scale factor will be sqrt(d_model) if True
           super().__init__(
               pad_token_id=__UpperCamelCase       ,    eos_token_id=__UpperCamelCase       ,    is_encoder_decoder=__UpperCamelCase       ,    decoder_start_token_id=__UpperCamelCase       ,    forced_eos_token_id=__UpperCamelCase       ,    **__UpperCamelCase       ,    )


      @property
      def 			__UpperCAmelCase		(						self						)->						int:
           return self.encoder_attention_heads


      @property
      def 			__UpperCAmelCase		(						self						)->						int:
           return self.d_model






