


import math
import sys




class A						:






      def __init__(      self		:  Optional[int]				)      ->		Optional[Any]:
             """simple docstring"""




             _lowerCamelCase :	Any						=0
             _lowerCamelCase :	Any						=[]
             _lowerCamelCase :	List[Any]						={}  # To store the pos of node in array






      def  lowerCamelCase (      self		:  int				)      ->		List[Any]:
             """simple docstring"""




             return self.cur_size == 0






      def  lowerCamelCase (      self		:  Optional[int]    ,     lowercase_		:  Union[str, Any]				)      ->		Optional[int]:
             """simple docstring"""




             _lowerCamelCase :	Tuple						=self.left(lowercase_				)
             _lowerCamelCase :	Union[str, Any]						=self.right(lowercase_				)
             if lc < self.cur_size and self.array(lowercase_				)[0] < self.array(lowercase_				)[0]:
                    _lowerCamelCase :	Optional[Any]						=lc
             else:
                    _lowerCamelCase :	Dict						=idx
             if rc < self.cur_size and self.array(lowercase_				)[0] < self.array(lowercase_				)[0]:
                    _lowerCamelCase :	Any						=rc
             if smallest != idx:
                    self.swap(lowercase_    ,     lowercase_				)
                    self.min_heapify(lowercase_				)






      def  lowerCamelCase (      self		:  Tuple    ,     lowercase_		:  Optional[int]				)      ->		List[Any]:
             """simple docstring"""




             _lowerCamelCase :	Tuple						=self.cur_size
             self.cur_size += 1
             self.array.append((sys.maxsize, tup[1])				)
             self.decrease_key((sys.maxsize, tup[1])    ,     tup[0]				)






      def  lowerCamelCase (      self		:  Dict				)      ->		Dict:
             """simple docstring"""




             _lowerCamelCase :	Tuple						=self.array[0][1]
             _lowerCamelCase :	int						=self.array[self.cur_size - 1]
             self.cur_size -= 1
             self.min_heapify(1				)
             del self.pos[min_node]
             return min_node






      def  lowerCamelCase (      self		:  List[str]    ,     lowercase_		:  str				)      ->		int:
             """simple docstring"""




             return 2 * i + 1






      def  lowerCamelCase (      self		:  Dict    ,     lowercase_		:  Optional[int]				)      ->		Any:
             """simple docstring"""




             return 2 * i + 2






      def  lowerCamelCase (      self		:  Union[str, Any]    ,     lowercase_		:  Optional[Any]				)      ->		Tuple:
             """simple docstring"""




             return math.floor(i / 2				)






      def  lowerCamelCase (      self		:  Any    ,     lowercase_		:  Tuple    ,     lowercase_		:  Any				)      ->		Dict:
             """simple docstring"""




             _lowerCamelCase :	Any						=j
             _lowerCamelCase :	List[str]						=i
             _lowerCamelCase :	Tuple						=self.array[i]
             _lowerCamelCase :	int						=self.array[j]
             _lowerCamelCase :	List[Any]						=temp






      def  lowerCamelCase (      self		:  Optional[Any]    ,     lowercase_		:  List[Any]    ,     lowercase_		:  Union[str, Any]				)      ->		List[Any]:
             """simple docstring"""




             _lowerCamelCase :	List[str]						=self.pos[tup[1]]
             # assuming the new_d is atmost old_d
             _lowerCamelCase :	Optional[Any]						=(new_d, tup[1])
             while idx > 0 and self.array[self.par(lowercase_				)][0] > self.array[idx][0]:
                    self.swap(lowercase_    ,     self.par(lowercase_				)				)
                    _lowerCamelCase :	List[str]						=self.par(lowercase_				)




class A						:






      def __init__(      self		:  List[str]    ,     lowercase_		:  List[str]				)      ->		Any:
             """simple docstring"""




             _lowerCamelCase :	List[str]						={}  # To store graph: u -> (v,w)
             _lowerCamelCase :	str						=num  # Number of nodes in graph
             # To store the distance from source vertex
             _lowerCamelCase :	List[str]						=[0] * self.num_nodes
             _lowerCamelCase :	int						=[-1] * self.num_nodes  # To store the path






      def  lowerCamelCase (      self		:  List[Any]    ,     lowercase_		:  Optional[Any]    ,     lowercase_		:  Union[str, Any]    ,     lowercase_		:  List[str]				)      ->		int:
             """simple docstring"""




             if u in self.adjList:
                    self.adjList[u].append((v, w)				)
             else:
                    _lowerCamelCase :	int						=[(v, w)]

             # Assuming undirected graph
             if v in self.adjList:
                    self.adjList[v].append((u, w)				)
             else:
                    _lowerCamelCase :	int						=[(u, w)]






      def  lowerCamelCase (      self		:  int				)      ->		int:
             """simple docstring"""




             for u in self.adjList:
                    print(lowercase_    ,     '->'    ,     ' -> '.join(str(F'''{v}({w})'''				) for v, w in self.adjList[u]				)				)






      def  lowerCamelCase (      self		:  Dict    ,     lowercase_		:  List[str]				)      ->		Dict:
             """simple docstring"""




             _lowerCamelCase :	Union[str, Any]						=[-1] * self.num_nodes
             # src is the source node
             _lowerCamelCase :	Optional[Any]						=0
             _lowerCamelCase :	str						=PriorityQueue()
             q.insert((0, src)				)  # (dist from src, node)
             for u in self.adjList:
                    if u != src:
                           _lowerCamelCase :	Any						=sys.maxsize  # Infinity
                           _lowerCamelCase :	Tuple						=-1

             while not q.is_empty():
                    _lowerCamelCase :	List[Any]						=q.extract_min()  # Returns node with the min dist from source
                    # Update the distance of all the neighbours of u and
                    # if their prev dist was INFINITY then push them in Q
                    for v, w in self.adjList[u]:
                           _lowerCamelCase :	List[str]						=self.dist[u] + w
                           if self.dist[v] > new_dist:
                                  if self.dist[v] == sys.maxsize:
                                         q.insert((new_dist, v)				)
                                  else:
                                         q.decrease_key((self.dist[v], v)    ,     lowercase_				)
                                  _lowerCamelCase :	str						=new_dist
                                  _lowerCamelCase :	Optional[int]						=u

        # Show the shortest distances from src
             self.show_distances(lowercase_				)






      def  lowerCamelCase (      self		:  Optional[int]    ,     lowercase_		:  Dict				)      ->		List[str]:
             """simple docstring"""




             print(F'''Distance from node: {src}'''				)
             for u in range(self.num_nodes				):
                    print(F'''Node {u} has distance: {self.dist[u]}'''				)






      def  lowerCamelCase (      self		:  str    ,     lowercase_		:  Union[str, Any]    ,     lowercase_		:  str				)      ->		Tuple:
             """simple docstring"""




             _lowerCamelCase :	Dict						=[]
             _lowerCamelCase :	Optional[Any]						=0
             _lowerCamelCase :	Any						=dest
             # Backtracking from dest to src
             while self.par[temp] != -1:
                    path.append(lowercase_				)
                    if temp != src:
                           for v, w in self.adjList[temp]:
                                  if v == self.par[temp]:
                                         cost += w
                                         break
                    _lowerCamelCase :	Optional[int]						=self.par[temp]
             path.append(lowercase_				)
             path.reverse()

             print(F'''----Path to reach {dest} from {src}----'''				)
             for u in path:
                    print(F'''{u}'''    ,     end=' '				)
                    if u != dest:
                           print('-> '    ,     end=''				)

             print('\nTotal cost of path: '    ,     lowercase_				)


if __name__ == "__main__":
 lowerCamelCase		      = Graph(9)
 graph.add_edge(0, 1, 4)
 graph.add_edge(0, 7, 8)
 graph.add_edge(1, 2, 8)
 graph.add_edge(1, 7, 11)
 graph.add_edge(2, 3, 7)
 graph.add_edge(2, 8, 2)
 graph.add_edge(2, 5, 4)
 graph.add_edge(3, 4, 9)
 graph.add_edge(3, 5, 14)
 graph.add_edge(4, 5, 10)
 graph.add_edge(5, 6, 2)
 graph.add_edge(6, 7, 1)
 graph.add_edge(6, 8, 6)
 graph.add_edge(7, 8, 7)
 graph.show_graph()
 graph.dijkstra(0)
 graph.show_path(0, 4)

# OUTPUT
# 0 -> 1(4) -> 7(8)
# 1 -> 0(4) -> 2(8) -> 7(11)
# 7 -> 0(8) -> 1(11) -> 6(1) -> 8(7)
# 2 -> 1(8) -> 3(7) -> 8(2) -> 5(4)
# 3 -> 2(7) -> 4(9) -> 5(14)
# 8 -> 2(2) -> 6(6) -> 7(7)
# 5 -> 2(4) -> 3(14) -> 4(10) -> 6(2)
# 4 -> 3(9) -> 5(10)
# 6 -> 5(2) -> 7(1) -> 8(6)
# Distance from node: 0
# Node 0 has distance: 0
# Node 1 has distance: 4
# Node 2 has distance: 12
# Node 3 has distance: 19
# Node 4 has distance: 21
# Node 5 has distance: 11
# Node 6 has distance: 9
# Node 7 has distance: 8
# Node 8 has distance: 14
# ----Path to reach 4 from 0----
# 0 -> 7 -> 6 -> 5 -> 4
# Total cost of path:  21






import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin




class A						(     UpperCamelCase_  ):
      UpperCamelCase__							:						Optional[Any]   ='AutoFeatureExtractor'
      UpperCamelCase__							:						List[str]   ='Speech2Text2Tokenizer'






      def __init__(      self		:  str    ,     lowercase_		:  Dict    ,     lowercase_		:  Optional[int]				)      ->		str:
             """simple docstring"""




             super().__init__(lowercase_    ,     lowercase_				)
             _lowerCamelCase :	Optional[Any]						=self.feature_extractor
             _lowerCamelCase :	Tuple						=False






      def __call__(      self		:  Tuple    ,     *lowercase_		:  str    ,     **lowercase_		:  List[Any]				)      ->		List[str]:
             """simple docstring"""




             if self._in_target_context_manager:
                    return self.current_processor(*lowercase_    ,     **lowercase_				)

             if "raw_speech" in kwargs:
                    warnings.warn('Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.'				)
                    _lowerCamelCase :	List[str]						=kwargs.pop('raw_speech'				)
             else:
                    _lowerCamelCase :	str						=kwargs.pop('audio'    ,     lowercase_				)
             _lowerCamelCase :	Optional[Any]						=kwargs.pop('sampling_rate'    ,     lowercase_				)
             _lowerCamelCase :	List[str]						=kwargs.pop('text'    ,     lowercase_				)
             if len(lowercase_				) > 0:
                    _lowerCamelCase :	Dict						=args[0]
                    _lowerCamelCase :	Optional[Any]						=args[1:]

             if audio is None and text is None:
                    raise ValueError('You need to specify either an `audio` or `text` input to process.'				)

             if audio is not None:
                    _lowerCamelCase :	List[Any]						=self.feature_extractor(lowercase_    ,     *lowercase_    ,     sampling_rate=lowercase_    ,     **lowercase_				)
             if text is not None:
                    _lowerCamelCase :	Tuple						=self.tokenizer(lowercase_    ,     **lowercase_				)

             if text is None:
                    return inputs
             elif audio is None:
                    return encodings
             else:
                    _lowerCamelCase :	Dict						=encodings['input_ids']
                    return inputs






      def  lowerCamelCase (      self		:  str    ,     *lowercase_		:  List[Any]    ,     **lowercase_		:  Any				)      ->		Union[str, Any]:
             """simple docstring"""




             return self.tokenizer.batch_decode(*lowercase_    ,     **lowercase_				)






      def  lowerCamelCase (      self		:  Optional[int]    ,     *lowercase_		:  Dict    ,     **lowercase_		:  Optional[int]				)      ->		str:
             """simple docstring"""




             return self.tokenizer.decode(*lowercase_    ,     **lowercase_				)






      @contextmanager
      def  lowerCamelCase (      self		:  Optional[Any]				)      ->		Tuple:
             """simple docstring"""




             warnings.warn(
                 '`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '
                 'labels by using the argument `text` of the regular `__call__` method (either in the same call as '
                 'your audio inputs, or in a separate call.'				)
             _lowerCamelCase :	Optional[Any]						=True
             _lowerCamelCase :	List[Any]						=self.tokenizer
             yield
             _lowerCamelCase :	Optional[int]						=self.feature_extractor
             _lowerCamelCase :	List[str]						=False


