





"""simple docstring"""





class 							snake_case							:

      '''simple docstring'''



      def __init__(							self       :      Optional[Any]						,				__lowercase       :      str = ""						,				__lowercase       :      bool = False ):


        '''simple docstring'''




        __UpperCAmelCase    :						dict[str, RadixNode]       =						{}

        # A node will be a leaf if the tree contains its word
        __UpperCAmelCase    :						Tuple       =						is_leaf

        __UpperCAmelCase    :						Tuple       =						prefix

      def       A_					(							self       :      Any						,				__lowercase       :      str ):


        '''simple docstring'''




        __UpperCAmelCase    :						Tuple       =						0
        for q, w in zip(self.prefix						,				__lowercase ):
          if q != w:
            break

          x += 1

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

      def       A_					(							self       :      Any						,				__lowercase       :      list[str] ):


        '''simple docstring'''




        for word in words:
          self.insert(__lowercase )

      def       A_					(							self       :      int						,				__lowercase       :      str ):


        '''simple docstring'''




        if self.prefix == word:
          __UpperCAmelCase    :						Union[str, 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:
          __UpperCAmelCase    :						Optional[Any]       =						RadixNode(prefix=__lowercase						,				is_leaf=__lowercase )

        else:
          __UpperCAmelCase    :						Optional[int]       =						self.nodes[word[0]]
          __UpperCAmelCase       ,     __UpperCAmelCase       ,     __UpperCAmelCase    :						Optional[Any]       =						incoming_node.match(
              __lowercase )

          # 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(__lowercase )

          # 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:
            __UpperCAmelCase    :						List[str]       =						remaining_prefix

            __UpperCAmelCase    :						Any       =						self.nodes[matching_string[0]]
            __UpperCAmelCase    :						Dict       =						RadixNode(__lowercase						,				__lowercase )
            __UpperCAmelCase    :						Dict       =						aux_node

            if remaining_word == "":
              __UpperCAmelCase    :						Any       =						True
            else:
              self.nodes[matching_string[0]].insert(__lowercase )

      def       A_					(							self       :      int						,				__lowercase       :      str ):


        '''simple docstring'''




        __UpperCAmelCase    :						Any       =						self.nodes.get(word[0]						,				__lowercase )
        if not incoming_node:
          return False
        else:
          __UpperCAmelCase       ,     __UpperCAmelCase       ,     __UpperCAmelCase    :						List[Any]       =						incoming_node.match(
              __lowercase )
          # 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(__lowercase )

      def       A_					(							self       :      int						,				__lowercase       :      str ):


        '''simple docstring'''




        __UpperCAmelCase    :						Any       =						self.nodes.get(word[0]						,				__lowercase )
        if not incoming_node:
          return False
        else:
          __UpperCAmelCase       ,     __UpperCAmelCase       ,     __UpperCAmelCase    :						Dict       =						incoming_node.match(
              __lowercase )
          # 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(__lowercase )
          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:
                  __UpperCAmelCase    :						str       =						list(self.nodes.values() )[0]
                  __UpperCAmelCase    :						Optional[int]       =						merging_node.is_leaf
                  self.prefix += merging_node.prefix
                  __UpperCAmelCase    :						Dict       =						merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
              elif len(incoming_node.nodes ) > 1:
                __UpperCAmelCase    :						Optional[int]       =						False
              # If there is 1 edge, we merge it with its child
              else:
                __UpperCAmelCase    :						Union[str, Any]       =						list(incoming_node.nodes.values() )[0]
                __UpperCAmelCase    :						Any       =						merging_node.is_leaf
                incoming_node.prefix += merging_node.prefix
                __UpperCAmelCase    :						Optional[Any]       =						merging_node.nodes

              return True







      def       A_					(							self       :      List[str]						,				__lowercase       :      int = 0 ):


        '''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       lowerCamelCase_       (   )						->bool:





  """simple docstring"""


  __UpperCAmelCase    :						str       =						'''banana bananas bandana band apple all beast'''.split()
  __UpperCAmelCase    :						Union[str, Any]       =						RadixNode()
  root.insert_many(UpperCAmelCase_  )

  assert all(root.find(UpperCAmelCase_  ) 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       lowerCamelCase_       (   )						->None:





  """simple docstring"""


  assert test_trie()


def       lowerCamelCase_       (   )						->None:





  """simple docstring"""


  __UpperCAmelCase    :						Union[str, Any]       =						RadixNode()
  __UpperCAmelCase    :						str       =						'''banana bananas bandanas bandana band apple all beast'''.split()
  root.insert_many(UpperCAmelCase_  )

  print('''Words:'''  ,			UpperCAmelCase_  )
  print('''Tree:'''  )
  root.print_tree()


if __name__ == "__main__":
  main()






"""simple docstring"""





import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  )						->Optional[Any]:





  """simple docstring"""


  __UpperCAmelCase    :						int       =						OmegaConf.load(UpperCAmelCase_  )
  __UpperCAmelCase    :						Union[str, Any]       =						torch.load(UpperCAmelCase_  ,			map_location='''cpu'''  )['''model''']
  __UpperCAmelCase    :						List[Any]       =						list(state_dict.keys()  )

  # extract state_dict for VQVAE
  __UpperCAmelCase    :						Dict       =						{}
  __UpperCAmelCase    :						Tuple       =						'''first_stage_model.'''
  for key in keys:
    if key.startswith(UpperCAmelCase_  ):
      __UpperCAmelCase    :						List[Any]       =						state_dict[key]

    # extract state_dict for UNetLDM
  __UpperCAmelCase    :						Union[str, Any]       =						{}
  __UpperCAmelCase    :						Any       =						'''model.diffusion_model.'''
  for key in keys:
    if key.startswith(UpperCAmelCase_  ):
      __UpperCAmelCase    :						int       =						state_dict[key]

  __UpperCAmelCase    :						Any       =						config.model.params.first_stage_config.params
  __UpperCAmelCase    :						Dict       =						config.model.params.unet_config.params

  __UpperCAmelCase    :						Tuple       =						VQModel(**UpperCAmelCase_  ).eval()
  vqvae.load_state_dict(UpperCAmelCase_  )

  __UpperCAmelCase    :						Any       =						UNetLDMModel(**UpperCAmelCase_  ).eval()
  unet.load_state_dict(UpperCAmelCase_  )

  __UpperCAmelCase    :						Union[str, Any]       =						DDIMScheduler(
      timesteps=config.model.params.timesteps  ,			beta_schedule='''scaled_linear'''  ,			beta_start=config.model.params.linear_start  ,			beta_end=config.model.params.linear_end  ,			clip_sample=UpperCAmelCase_  ,			)

  __UpperCAmelCase    :						Tuple       =						LDMPipeline(UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  )
  pipeline.save_pretrained(UpperCAmelCase_  )


if __name__ == "__main__":
  lowercase__				:str				   =       argparse.ArgumentParser()
  parser.add_argument('--checkpoint_path', type=str, required=True)
  parser.add_argument('--config_path', type=str, required=True)
  parser.add_argument('--output_path', type=str, required=True)
  lowercase__				:Dict				   =       parser.parse_args()

  convert_ldm_original(args.checkpoint_path, args.config_path, args.output_path)