'''simple docstring'''






class lowercase_       :







   """simple docstring"""

   def __init__(      self      :			Optional[int]     )  ->			None:
        _A    		=  {}  # Mapping from char to TrieNode
        _A    		=  False
   def 	__UpperCAmelCase   (      self      :			List[str], UpperCamelCase__      :			list[str]     )  ->			None:
        for word in words:
             self.insert(UpperCamelCase__     )
   def 	__UpperCAmelCase   (      self      :			Optional[int], UpperCamelCase__      :			str     )  ->			None:
        _A    		=  self
        for char in word:
             if char not in curr.nodes:
                  _A    		=  TrieNode()
             _A    		=  curr.nodes[char]
        _A    		=  True
   def 	__UpperCAmelCase   (      self      :			str, UpperCamelCase__      :			str     )  ->			bool:
        _A    		=  self
        for char in word:
             if char not in curr.nodes:
                  return False
             _A    		=  curr.nodes[char]
        return curr.is_leaf

   def 	__UpperCAmelCase   (      self      :			Union[str, Any], UpperCamelCase__      :			str     )  ->			None:

        def _delete(UpperCamelCase__      :			TrieNode, UpperCamelCase__      :			str, UpperCamelCase__      :			int     ) -> bool:
             if index == len(UpperCamelCase__     ):
                  # If word does not exist
                  if not curr.is_leaf:
                       return False
                  _A    		=  False
                  return len(curr.nodes     ) == 0
             _A    		=  word[index]
             _A    		=  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
             _A    		=  _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  _SCREAMING_SNAKE_CASE		(      __snake_case							:			TrieNode   ,		__snake_case							:			str				):
     if node.is_leaf:
          print(__snake_case   ,		end=' '				)

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





def  _SCREAMING_SNAKE_CASE		(      ):
     _A    		=  'banana bananas bandana band apple all beast'.split()
     _A    		=  TrieNode()
     root.insert_many(__snake_case				)
     # print_words(root, "")
     assert all(root.find(__snake_case				) 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		(      __snake_case							:			str   ,		__snake_case							:			bool				):
     print(str(__snake_case				)   ,		'works!' if passes else 'doesn\'t work :('				)





def  _SCREAMING_SNAKE_CASE		(      ):
     assert test_trie()





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


if __name__ == "__main__":
   main()







import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
    __snake_case   							=						argparse.ArgumentParser()

    parser.add_argument('''--dump_path''', default=None, type=str, required=True, help='''Path to the output model.''')

    parser.add_argument(
        '''--txt2img_unclip''',
        default='''kakaobrain/karlo-v1-alpha''',
        type=str,
        required=False,
        help='''The pretrained txt2img unclip.''',
    )

    __snake_case   							=						parser.parse_args()

    __snake_case   							=						UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

    __snake_case   							=						CLIPImageProcessor()
    __snake_case   							=						CLIPVisionModelWithProjection.from_pretrained('''openai/clip-vit-large-patch14''')

    __snake_case   							=						UnCLIPImageVariationPipeline(
        decoder=txtaimg.decoder,
        text_encoder=txtaimg.text_encoder,
        tokenizer=txtaimg.tokenizer,
        text_proj=txtaimg.text_proj,
        feature_extractor=feature_extractor,
        image_encoder=image_encoder,
        super_res_first=txtaimg.super_res_first,
        super_res_last=txtaimg.super_res_last,
        decoder_scheduler=txtaimg.decoder_scheduler,
        super_res_scheduler=txtaimg.super_res_scheduler,
    )

    imgaimg.save_pretrained(args.dump_path)


