






"""simple docstring"""



import math
import sys


class 	_UpperCamelCase :



    '''simple docstring'''


    def __init__(      self			):
     UpperCAmelCase__ 						=				0
     UpperCAmelCase__ 						=				[]
     UpperCAmelCase__ 						=				{}  # To store the pos of node in array


    def 		A__      (      self			):
     return self.cur_size == 0


    def 		A__      (      self   ,			__lowercase			):
     UpperCAmelCase__ 						=				self.left(_snake_case			)
     UpperCAmelCase__ 						=				self.right(_snake_case			)
     if lc < self.cur_size and self.array(_snake_case			)[0] < self.array(_snake_case			)[0]:
      UpperCAmelCase__ 						=				lc
     else:
      UpperCAmelCase__ 						=				idx
     if rc < self.cur_size and self.array(_snake_case			)[0] < self.array(_snake_case			)[0]:
      UpperCAmelCase__ 						=				rc
     if smallest != idx:
      self.swap(_snake_case   ,			_snake_case			)
      self.min_heapify(_snake_case			)


    def 		A__      (      self   ,			__lowercase			):
     # Inserts a node into the Priority Queue
     UpperCAmelCase__ 						=				self.cur_size
     self.cur_size += 1
     self.array.append((sys.maxsize, tup[1])			)
     self.decrease_key((sys.maxsize, tup[1])   ,			tup[0]			)


    def 		A__      (      self			):
     # Removes and returns the min element at top of priority queue
     UpperCAmelCase__ 						=				self.array[0][1]
     UpperCAmelCase__ 						=				self.array[self.cur_size - 1]
     self.cur_size -= 1
     self.min_heapify(1			)
     del self.pos[min_node]
     return min_node


    def 		A__      (      self   ,			__lowercase			):
     # returns the index of left child
     return 2 * i + 1


    def 		A__      (      self   ,			__lowercase			):
     # returns the index of right child
     return 2 * i + 2


    def 		A__      (      self   ,			__lowercase			):
     # returns the index of parent
     return math.floor(i / 2			)


    def 		A__      (      self   ,			__lowercase   ,			__lowercase			):
     # swaps array elements at indices i and j
     # update the pos{}
     UpperCAmelCase__ 						=				j
     UpperCAmelCase__ 						=				i
     UpperCAmelCase__ 						=				self.array[i]
     UpperCAmelCase__ 						=				self.array[j]
     UpperCAmelCase__ 						=				temp






    def 		A__      (      self   ,			__lowercase   ,			__lowercase			):
     UpperCAmelCase__ 						=				self.pos[tup[1]]
     # assuming the new_d is atmost old_d
     UpperCAmelCase__ 						=				(new_d, tup[1])
     while idx > 0 and self.array[self.par(_snake_case			)][0] > self.array[idx][0]:
      self.swap(_snake_case   ,			self.par(_snake_case			)			)
      UpperCAmelCase__ 						=				self.par(_snake_case			)



class 	_UpperCamelCase :



    '''simple docstring'''


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


    def 		A__      (      self   ,			__lowercase   ,			__lowercase   ,			__lowercase			):
     #  Edge going from node u to v and v to u with weight w
     # u (w)-> v, v (w) -> u
     # Check if u already in graph
     if u in self.adjList:
      self.adjList[u].append((v, w)			)
     else:
      UpperCAmelCase__ 						=				[(v, w)]

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


    def 		A__      (      self			):
     # u -> v(w)
     for u in self.adjList:
      print(_snake_case   ,			"""->"""   ,			""" -> """.join(str(F'''{v}({w})'''			) for v, w in self.adjList[u]			)			)


    def 		A__      (      self   ,			__lowercase			):
     # Flush old junk values in par[]
     UpperCAmelCase__ 						=				[-1] * self.num_nodes
     # src is the source node
     UpperCAmelCase__ 						=				0
     UpperCAmelCase__ 						=				PriorityQueue()
     q.insert((0, src)			)  # (dist from src, node)
     for u in self.adjList:
      if u != src:
       UpperCAmelCase__ 						=				sys.maxsize  # Infinity
       UpperCAmelCase__ 						=				-1

     while not q.is_empty():
      UpperCAmelCase__ 						=				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]:
       UpperCAmelCase__ 						=				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)   ,			_snake_case			)
        UpperCAmelCase__ 						=				new_dist
        UpperCAmelCase__ 						=				u

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


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






    def 		A__      (      self   ,			__lowercase   ,			__lowercase			):
     # To show the shortest path from src to dest
     # WARNING: Use it *after* calling dijkstra
     UpperCAmelCase__ 						=				[]
     UpperCAmelCase__ 						=				0
     UpperCAmelCase__ 						=				dest
     # Backtracking from dest to src
     while self.par[temp] != -1:
      path.append(_snake_case			)
      if temp != src:
       for v, w in self.adjList[temp]:
        if v == self.par[temp]:
         cost += w
         break
      UpperCAmelCase__ 						=				self.par[temp]
     path.append(_snake_case			)
     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: """   ,			_snake_case			)


if __name__ == "__main__":
 a  :						Dict					       =							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






'''simple docstring'''


import unittest

from transformers import is_torch_available, load_tool

from .test_tools_common import ToolTesterMixin


if is_torch_available():
						import torch



class        lowercase    (	unittest.TestCase,       a_			):


							def     _snake_case				(      self)				->					Optional[int]:
								UpperCAmelCase_		:   int													=       load_tool('speech-to-text')
								self.tool.setup()


							def     _snake_case				(      self)				->					Any:
								UpperCAmelCase_		:   str													=       self.tool(torch.ones(3000))
								self.assertEqual(_snake_case     ,      ' you')





							def     _snake_case				(      self)				->					str:
								UpperCAmelCase_		:   List[Any]													=       self.tool(audio=torch.ones(3000))
								self.assertEqual(_snake_case     ,      ' you')






