

"""simple docstring"""


import unittest

from transformers import DonutProcessor


__A						   =			"naver-clova-ix/donut-base"





class     snake_case	(				unittest.TestCase  ):

				def 							lowercase_     (	self							:				List[str])->   Any:



						'''simple docstring'''


						__lowerCAmelCase:       List[str]          =			DonutProcessor.from_pretrained(UpperCamelCase__)




				def 							lowercase_     (	self							:				Any)->   Union[str, Any]:



						'''simple docstring'''


						__lowerCAmelCase:       int          =			{
						    """name""": """John Doe""",
						    """age""": """99""",
						    """city""": """Atlanta""",
						    """state""": """GA""",
						    """zip""": """30301""",
						    """phone""": """123-4567""",
						    """nicknames""": [{"""nickname""": """Johnny"""}, {"""nickname""": """JD"""}],
						}

						__lowerCAmelCase:       Tuple          =			(
						    """<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>"""
						    """<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>"""
						    """<s_nicknames><s_nickname>Johnny</s_nickname>"""
						    """<sep/><s_nickname>JD</s_nickname></s_nicknames>"""
						)
						__lowerCAmelCase:       Dict          =			self.processor.tokenajson(UpperCamelCase__)

						self.assertDictEqual(UpperCamelCase__     ,  UpperCamelCase__)









from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

__UpperCAmelCase       :   str				       =							TypeVar("T")







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    int:
  return (position - 1) // 2







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    int:
  return (2 * position) + 1







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    int:
  return (2 * position) + 2







class     __snake_case       (							Generic[T]			):





       '''simple docstring'''







       def __init__(  self :    Tuple		):
         __snake_case:						list[tuple[T, int]]   =						[]
         __snake_case:						dict[T, int]   =						{}
         __snake_case:						int   =						0




       def __len__(  self :    Tuple		):
         return self.elements




       def __repr__(  self :    Optional[int]		):
         return str(self.heap		)




       def 							UpperCAmelCase__ (  self :    List[Any]		):
         # Check if the priority queue is empty
         return self.elements == 0




       def 							UpperCAmelCase__ (  self :    List[Any]							,				A :    T							,				A :    int		):
         # Add an element with given priority to the queue
         self.heap.append((elem, weight)		)
         __snake_case:						Optional[Any]   =						self.elements
         self.elements += 1
         self._bubble_up(A		)




       def 							UpperCAmelCase__ (  self :    List[Any]		):
         # Remove and return the element with lowest weight (highest priority)
         if self.elements > 1:
           self._swap_nodes(0							,				self.elements - 1		)
         __snake_case  ,   __snake_case:						Union[str, Any]   =						self.heap.pop()
         del self.position_map[elem]
         self.elements -= 1
         if self.elements > 0:
           __snake_case  ,   __snake_case:						int   =						self.heap[0]
           self._bubble_down(A		)
         return elem




       def 							UpperCAmelCase__ (  self :    Any							,				A :    T							,				A :    int		):
         # Update the weight of the given key
         __snake_case:						Dict   =						self.position_map[elem]
         __snake_case:						Optional[Any]   =						(elem, weight)
         if position > 0:
           __snake_case:						Optional[int]   =						get_parent_position(A		)
           __snake_case  ,   __snake_case:						Dict   =						self.heap[parent_position]
           if parent_weight > weight:
             self._bubble_up(A		)
           else:
             self._bubble_down(A		)
         else:
           self._bubble_down(A		)




       def 							UpperCAmelCase__ (  self :    int							,				A :    T		):
         # Place a node at the proper position (upward movement) [to be used internally
         # only]
         __snake_case:						int   =						self.position_map[elem]
         if curr_pos == 0:
           return None
         __snake_case:						Optional[Any]   =						get_parent_position(A		)
         __snake_case  ,   __snake_case:						Tuple   =						self.heap[curr_pos]
         __snake_case  ,   __snake_case:						Optional[Any]   =						self.heap[parent_position]
         if parent_weight > weight:
           self._swap_nodes(A							,				A		)
           return self._bubble_up(A		)
         return None




       def 							UpperCAmelCase__ (  self :    List[str]							,				A :    T		):
         # Place a node at the proper position (downward movement) [to be used
         # internally only]
         __snake_case:						Any   =						self.position_map[elem]
         __snake_case  ,   __snake_case:						int   =						self.heap[curr_pos]
         __snake_case:						Union[str, Any]   =						get_child_left_position(A		)
         __snake_case:						Dict   =						get_child_right_position(A		)
         if child_left_position < self.elements and child_right_position < self.elements:
           __snake_case  ,   __snake_case:						Any   =						self.heap[child_left_position]
           __snake_case  ,   __snake_case:						List[str]   =						self.heap[child_right_position]
           if child_right_weight < child_left_weight and child_right_weight < weight:
             self._swap_nodes(A							,				A		)
             return self._bubble_down(A		)
         if child_left_position < self.elements:
           __snake_case  ,   __snake_case:						List[Any]   =						self.heap[child_left_position]
           if child_left_weight < weight:
             self._swap_nodes(A							,				A		)
             return self._bubble_down(A		)
         else:
           return None
         if child_right_position < self.elements:
           __snake_case  ,   __snake_case:						List[Any]   =						self.heap[child_right_position]
           if child_right_weight < weight:
             self._swap_nodes(A							,				A		)
             return self._bubble_down(A		)
         return None






       def 							UpperCAmelCase__ (  self :    int							,				A :    int							,				A :    int		):
         # Swap the nodes at the given positions
         __snake_case:						Optional[int]   =						self.heap[nodea_pos][0]
         __snake_case:						Optional[Any]   =						self.heap[nodea_pos][0]
         __snake_case  ,   __snake_case:						Tuple   =						(
             self.heap[nodea_pos],
             self.heap[nodea_pos],
         )
         __snake_case:						Any   =						nodea_pos
         __snake_case:						str   =						nodea_pos







class     __snake_case       (							Generic[T]			):





       '''simple docstring'''







       def __init__(  self :    Any		):
         __snake_case:						dict[T, dict[T, int]]   =						{}
         __snake_case:						int   =						0




       def __repr__(  self :    Dict		):
         return str(self.connections		)




       def __len__(  self :    List[str]		):
         return self.nodes




       def 							UpperCAmelCase__ (  self :    Optional[Any]							,				A :    T		):
         # Add a node in the graph if it is not in the graph
         if node not in self.connections:
           __snake_case:						List[str]   =						{}
           self.nodes += 1






       def 							UpperCAmelCase__ (  self :    Optional[Any]							,				A :    T							,				A :    T							,				A :    int		):
         # Add an edge between 2 nodes in the graph
         self.add_node(A		)
         self.add_node(A		)
         __snake_case:						Optional[Any]   =						weight
         __snake_case:						str   =						weight







def 			A__							(    SCREAMING_SNAKE_CASE__					,					)   ->    tuple[dict[T, int], dict[T, T | None]]:
  __snake_case:						dict[T, int]   =						{node: maxsize for node in graph.connections}
  __snake_case:						dict[T, T | None]   =						{node: None for node in graph.connections}

  __snake_case:						MinPriorityQueue[T]   =						MinPriorityQueue()
  for node, weight in dist.items():
    priority_queue.push(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)

  if priority_queue.is_empty():
    return dist, parent

  # initialization
  __snake_case:						Optional[int]   =						priority_queue.extract_min()
  __snake_case:						Any   =						0
  for neighbour in graph.connections[node]:
    if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
      __snake_case:						Tuple   =						dist[node] + graph.connections[node][neighbour]
      priority_queue.update_key(SCREAMING_SNAKE_CASE__					,					dist[neighbour])
      __snake_case:						Optional[int]   =						node

    # running prim's algorithm
  while not priority_queue.is_empty():
    __snake_case:						Optional[int]   =						priority_queue.extract_min()
    for neighbour in graph.connections[node]:
      if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
        __snake_case:						Tuple   =						dist[node] + graph.connections[node][neighbour]
        priority_queue.update_key(SCREAMING_SNAKE_CASE__					,					dist[neighbour])
        __snake_case:						List[Any]   =						node
  return dist, parent






