

'''simple docstring'''


import math
import sys



class        lowercase    :


							def __init__(      self)				->					List[str]:
								UpperCAmelCase_		:   Union[str, Any]													=       0
								UpperCAmelCase_		:   Optional[int]													=       []
								UpperCAmelCase_		:   List[str]													=       {}  # To store the pos of node in array


							def     _snake_case				(      self)				->					str:
								return self.cur_size == 0


							def     _snake_case				(      self     ,      _snake_case)				->					str:
								UpperCAmelCase_		:   Optional[int]													=       self.left(_snake_case)
								UpperCAmelCase_		:   Optional[int]													=       self.right(_snake_case)
								if lc < self.cur_size and self.array(_snake_case)[0] < self.array(_snake_case)[0]:
									UpperCAmelCase_		:   List[Any]													=       lc
								else:
									UpperCAmelCase_		:   Dict													=       idx
								if rc < self.cur_size and self.array(_snake_case)[0] < self.array(_snake_case)[0]:
									UpperCAmelCase_		:   Tuple													=       rc
								if smallest != idx:
									self.swap(_snake_case     ,      _snake_case)
									self.min_heapify(_snake_case)


							def     _snake_case				(      self     ,      _snake_case)				->					Optional[int]:
								# Inserts a node into the Priority Queue
								UpperCAmelCase_		:   List[str]													=       self.cur_size
								self.cur_size += 1
								self.array.append((sys.maxsize, tup[1]))
								self.decrease_key((sys.maxsize, tup[1])     ,      tup[0])


							def     _snake_case				(      self)				->					Union[str, Any]:
								# Removes and returns the min element at top of priority queue
								UpperCAmelCase_		:   str													=       self.array[0][1]
								UpperCAmelCase_		:   Any													=       self.array[self.cur_size - 1]
								self.cur_size -= 1
								self.min_heapify(1)
								del self.pos[min_node]
								return min_node


							def     _snake_case				(      self     ,      _snake_case)				->					Optional[int]:
								# returns the index of left child
								return 2 * i + 1


							def     _snake_case				(      self     ,      _snake_case)				->					List[Any]:
								# returns the index of right child
								return 2 * i + 2


							def     _snake_case				(      self     ,      _snake_case)				->					Tuple:
								# returns the index of parent
								return math.floor(i / 2)


							def     _snake_case				(      self     ,      _snake_case     ,      _snake_case)				->					Optional[int]:
								# swaps array elements at indices i and j
								# update the pos{}
								UpperCAmelCase_		:   List[Any]													=       j
								UpperCAmelCase_		:   Tuple													=       i
								UpperCAmelCase_		:   List[str]													=       self.array[i]
								UpperCAmelCase_		:   Tuple													=       self.array[j]
								UpperCAmelCase_		:   int													=       temp





							def     _snake_case				(      self     ,      _snake_case     ,      _snake_case)				->					List[Any]:
								UpperCAmelCase_		:   int													=       self.pos[tup[1]]
								# assuming the new_d is atmost old_d
								UpperCAmelCase_		:   int													=       (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_		:   Optional[int]													=       self.par(_snake_case)



class        lowercase    :


							def __init__(      self     ,      _snake_case)				->					Tuple:
								UpperCAmelCase_		:   Dict													=       {}  # To store graph: u -> (v,w)
								UpperCAmelCase_		:   str													=       num  # Number of nodes in graph
								# To store the distance from source vertex
								UpperCAmelCase_		:   Optional[Any]													=       [0] * self.num_nodes
								UpperCAmelCase_		:   List[Any]													=       [-1] * self.num_nodes  # To store the path


							def     _snake_case				(      self     ,      _snake_case     ,      _snake_case     ,      _snake_case)				->					int:
								#  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_		:   Optional[int]													=       [(v, w)]

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


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


							def     _snake_case				(      self     ,      _snake_case)				->					Dict:
								# Flush old junk values in par[]
								UpperCAmelCase_		:   Optional[int]													=       [-1] * self.num_nodes
								# src is the source node
								UpperCAmelCase_		:   Optional[int]													=       0
								UpperCAmelCase_		:   str													=       PriorityQueue()
								q.insert((0, src))  # (dist from src, node)
								for u in self.adjList:
									if u != src:
										UpperCAmelCase_		:   List[str]													=       sys.maxsize  # Infinity
										UpperCAmelCase_		:   Any													=       -1

								while not q.is_empty():
									UpperCAmelCase_		:   Optional[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]:
										UpperCAmelCase_		:   Optional[Any]													=       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_		:   Optional[int]													=       new_dist
											UpperCAmelCase_		:   Union[str, Any]													=       u

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


							def     _snake_case				(      self     ,      _snake_case)				->					List[Any]:
								print(F"""Distance from node: {src}""")
								for u in range(self.num_nodes):
									print(F"""Node {u} has distance: {self.dist[u]}""")





							def     _snake_case				(      self     ,      _snake_case     ,      _snake_case)				->					str:
								# To show the shortest path from src to dest
								# WARNING: Use it *after* calling dijkstra
								UpperCAmelCase_		:   Any													=       []
								UpperCAmelCase_		:   List[Any]													=       0
								UpperCAmelCase_		:   Optional[int]													=       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_		:   Tuple													=       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__":
						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









'''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')






