






from __future__ import annotations

from queue import Queue
def 		_a					(   a				:int			,							a				:int				)							->    tuple[int, int]:
 a ^= b
 b ^= a
 a ^= b
 return a, b
def 		_a					(   a				:int			,							a				:list[list[int]]				)							->    list[list[int]]:
 a							=   1
 while (1 << j) < max_node:
  for i in range(1			,							max_node + 1				):
   a							=   parent[j - 1][parent[j - 1][i]]
  j += 1
 return parent
def 		_a					(   a				:int			,							a				:int			,							a				:list[int]			,							a				:list[list[int]]				)							->    int:
 # u must be deeper in the tree than v
 if level[u] < level[v]:
  a						,  a							=   swap(a			,							a				)
 # making depth of u same as depth of v
 for i in range(18			,							-1			,							-1				):
  if level[u] - (1 << i) >= level[v]:
   a							=   parent[i][u]
    # at the same depth if u==v that mean lca is found
 if u == v:
  return u
 # moving both nodes upwards till lca in found
 for i in range(18			,							-1			,							-1				):
  if parent[i][u] not in [0, parent[i][v]]:
   a						,  a							=   parent[i][u], parent[i][v]
    # returning longest common ancestor of u,v
 return parent[0][u]
def 		_a					(   a				:list[int]			,							a				:list[list[int]]			,							a				:int			,							a				:dict[int, list[int]]			,							a				:int = 1			,							)							->    tuple[list[int], list[list[int]]]:
 a							=   0
 a							=   Queue(maxsize=a				)
 q.put(a				)
 while q.qsize() != 0:
  a							=   q.get()
  for v in graph[u]:
   if level[v] == -1:
    a							=   level[u] + 1
    q.put(a				)
    a							=   u
 return level, parent
def 		_a					(   )							->    None:
 a							=   13
 # initializing with 0
 a							=   [[0 for _ in range(max_node + 10				)] for _ in range(20				)]
 # initializing with -1 which means every node is unvisited
 a							=   [-1 for _ in range(max_node + 10				)]
 a							=   {
     1: [2, 3, 4],
     2: [5],
     3: [6, 7],
     4: [8],
     5: [9, 10],
     6: [11],
     7: [],
     8: [12, 13],
     9: [],
     10: [],
     11: [],
     12: [],
     13: [],
 }
 a						,  a							=   breadth_first_search(a			,							a			,							a			,							a			,							1				)
 a							=   create_sparse(a			,							a				)
 print('''LCA of node 1 and 3 is: '''			,							lowest_common_ancestor(1			,							3			,							a			,							a				)				)
 print('''LCA of node 5 and 6 is: '''			,							lowest_common_ancestor(5			,							6			,							a			,							a				)				)
 print('''LCA of node 7 and 11 is: '''			,							lowest_common_ancestor(7			,							11			,							a			,							a				)				)
 print('''LCA of node 6 and 7 is: '''			,							lowest_common_ancestor(6			,							7			,							a			,							a				)				)
 print('''LCA of node 4 and 12 is: '''			,							lowest_common_ancestor(4			,							12			,							a			,							a				)				)
 print('''LCA of node 8 and 8 is: '''			,							lowest_common_ancestor(8			,							8			,							a			,							a				)				)


if __name__ == "__main__":
     main()










from ...utils import is_transformers_available
from .pipeline_latent_diffusion_superresolution import LDMSuperResolutionPipeline


if is_transformers_available():
     from .pipeline_latent_diffusion import LDMBertModel, LDMTextToImagePipeline


