
class      __A:

  """simple docstring"""







  def __init__(self	,      SCREAMING_SNAKE_CASE_ = ""	,      SCREAMING_SNAKE_CASE_ = False						):
       # Mapping from the first character of the prefix of the node
       UpperCamelCase__				=    {}

       # A node will be a leaf if the tree contains its word
       UpperCamelCase__				=    is_leaf

       UpperCamelCase__				=    prefix







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    0
       for q, w in zip(self.prefix	,      SCREAMING_SNAKE_CASE_						):
            if q != w:
                 break

            x += 1

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







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       for word in words:
            self.insert(SCREAMING_SNAKE_CASE_						)







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       # Case 1: If the word is the prefix of the node
       # Solution: We set the current node as leaf
       if self.prefix == word:
            UpperCamelCase__				=    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__				=    RadixNode(prefix=SCREAMING_SNAKE_CASE_	,      is_leaf=SCREAMING_SNAKE_CASE_						)

       else:
            UpperCamelCase__				=    self.nodes[word[0]]
            UpperCamelCase__		,	UpperCamelCase__		,	UpperCamelCase__				=    incoming_node.match(
                SCREAMING_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(SCREAMING_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:
                 UpperCamelCase__				=    remaining_prefix

                 UpperCamelCase__				=    self.nodes[matching_string[0]]
                 UpperCamelCase__				=    RadixNode(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						)
                 UpperCamelCase__				=    aux_node

                 if remaining_word == "":
                      UpperCamelCase__				=    True
                 else:
                      self.nodes[matching_string[0]].insert(SCREAMING_SNAKE_CASE_						)







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    self.nodes.get(word[0]	,      SCREAMING_SNAKE_CASE_						)
       if not incoming_node:
            return False
       else:
            UpperCamelCase__		,	UpperCamelCase__		,	UpperCamelCase__				=    incoming_node.match(
                SCREAMING_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(SCREAMING_SNAKE_CASE_						)







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    self.nodes.get(word[0]	,      SCREAMING_SNAKE_CASE_						)
       if not incoming_node:
            return False
       else:
            UpperCamelCase__		,	UpperCamelCase__		,	UpperCamelCase__				=    incoming_node.match(
                SCREAMING_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(SCREAMING_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:
                                UpperCamelCase__				=    list(self.nodes.values()						)[0]
                                UpperCamelCase__				=    merging_node.is_leaf
                                self.prefix += merging_node.prefix
                                UpperCamelCase__				=    merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
                      elif len(incoming_node.nodes						) > 1:
                           UpperCamelCase__				=    False
                      # If there is 1 edge, we merge it with its child
                      else:
                           UpperCamelCase__				=    list(incoming_node.nodes.values()						)[0]
                           UpperCamelCase__				=    merging_node.is_leaf
                           incoming_node.prefix += merging_node.prefix
                           UpperCamelCase__				=    merging_node.nodes

                      return True







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_ = 0						):
       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 						__magic_name__			(   ):



     '''simple docstring'''




     UpperCamelCase__				=    """banana bananas bandana band apple all beast""".split()
     UpperCamelCase__				=    RadixNode()
     root.insert_many(__a						)

     assert all(root.find(__a						) 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 						__magic_name__			(   ):



     '''simple docstring'''




     assert test_trie()






def 						__magic_name__			(   ):



     '''simple docstring'''




     UpperCamelCase__				=    RadixNode()
     UpperCamelCase__				=    """banana bananas bandanas bandana band apple all beast""".split()
     root.insert_many(__a						)

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


if __name__ == "__main__":
    main()







import re

import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey

from ..utils import logging


lowerCamelCase_						     =					logging.get_logger(__name__)






def 						__magic_name__			(   __a      :	Optional[int]						):



     '''simple docstring'''




     UpperCamelCase__				=    R"""\w+[.]\d+"""
     UpperCamelCase__				=    re.findall(__a	,		__a						)
     for pat in pats:
          UpperCamelCase__				=    key.replace(__a	,		"""_""".join(pat.split("""."""						)						)						)
     return key






def 						__magic_name__			(   __a      :	str	,		__a      :	Dict	,		__a      :	int						):



     '''simple docstring'''




     UpperCamelCase__				=    pt_tuple_key[:-1] + ("""scale""",)
     if (
         any("""norm""" in str_ for str_ in pt_tuple_key						)
         and (pt_tuple_key[-1] == "bias")
         and (pt_tuple_key[:-1] + ("bias",) not in random_flax_state_dict)
         and (pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict)
     ):
          UpperCamelCase__				=    pt_tuple_key[:-1] + ("""scale""",)
          return renamed_pt_tuple_key, pt_tensor
     elif pt_tuple_key[-1] in ["weight", "gamma"] and pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict:
          UpperCamelCase__				=    pt_tuple_key[:-1] + ("""scale""",)
          return renamed_pt_tuple_key, pt_tensor

     # embedding
     if pt_tuple_key[-1] == "weight" and pt_tuple_key[:-1] + ("embedding",) in random_flax_state_dict:
          UpperCamelCase__				=    pt_tuple_key[:-1] + ("""embedding""",)
          return renamed_pt_tuple_key, pt_tensor

     # conv layer
     UpperCamelCase__				=    pt_tuple_key[:-1] + ("""kernel""",)
     if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
          UpperCamelCase__				=    pt_tensor.transpose(2	,		3	,		1	,		0						)
          return renamed_pt_tuple_key, pt_tensor

     # linear layer
     UpperCamelCase__				=    pt_tuple_key[:-1] + ("""kernel""",)
     if pt_tuple_key[-1] == "weight":
          UpperCamelCase__				=    pt_tensor.T
          return renamed_pt_tuple_key, pt_tensor

     # old PyTorch layer norm weight
     UpperCamelCase__				=    pt_tuple_key[:-1] + ("""weight""",)
     if pt_tuple_key[-1] == "gamma":
          return renamed_pt_tuple_key, pt_tensor

     # old PyTorch layer norm bias
     UpperCamelCase__				=    pt_tuple_key[:-1] + ("""bias""",)
     if pt_tuple_key[-1] == "beta":
          return renamed_pt_tuple_key, pt_tensor

     return pt_tuple_key, pt_tensor






def 						__magic_name__			(   __a      :	List[Any]	,		__a      :	List[Any]	,		__a      :	Optional[int]=42						):



     '''simple docstring'''




     UpperCamelCase__				=    {k: v.numpy() for k, v in pt_state_dict.items()}

     # Step 2: Since the model is stateless, get random Flax params
     UpperCamelCase__				=    flax_model.init_weights(PRNGKey(__a						)						)

     UpperCamelCase__				=    flatten_dict(__a						)
     UpperCamelCase__				=    {}

     # Need to change some parameters name to match Flax names
     for pt_key, pt_tensor in pt_state_dict.items():
          UpperCamelCase__				=    rename_key(__a						)
          UpperCamelCase__				=    tuple(renamed_pt_key.split("""."""						)						)

          # Correctly rename weight parameters
          UpperCamelCase__		,	UpperCamelCase__				=    rename_key_and_reshape_tensor(__a	,		__a	,		__a						)

          if flax_key in random_flax_state_dict:
               if flax_tensor.shape != random_flax_state_dict[flax_key].shape:
                    raise ValueError(
                        f"PyTorch checkpoint seems to be incorrect. Weight {pt_key} was expected to be of shape "
                        f"{random_flax_state_dict[flax_key].shape}, but is {flax_tensor.shape}."						)

        # also add unexpected weight so that warning is thrown
          UpperCamelCase__				=    jnp.asarray(__a						)

     return unflatten_dict(__a						)





