






from __future__ import annotations

import time

snake_case__      :	Union[str, Any]       	=      list[tuple[int, int]]

snake_case__      :	Any       	=      [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

snake_case__      :	List[str]       	=      [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right


class 						_a       :






  """simple docstring"""





  def __init__(     self		,		_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase )			-> Optional[Any]:
     UpperCamelCase_									=     pos_x
     UpperCamelCase_									=     pos_y
     UpperCamelCase_									=     (pos_y, pos_x)
     UpperCamelCase_									=     goal_x
     UpperCamelCase_									=     goal_y
     UpperCamelCase_									=     parent




class 						_a       :






  """simple docstring"""





  def __init__(     self		,		_UpperCAmelCase		,		_UpperCAmelCase )			-> Union[str, Any]:
     UpperCamelCase_									=     Node(start[1]		,		start[0]		,		goal[1]		,		goal[0]		,		_UpperCAmelCase )
     UpperCamelCase_									=     Node(goal[1]		,		goal[0]		,		goal[1]		,		goal[0]		,		_UpperCAmelCase )

     UpperCamelCase_									=     [self.start]
     UpperCamelCase_									=     False




  def    _UpperCAmelCase     (     self )			-> Path | None:
     while self.node_queue:
        UpperCamelCase_									=     self.node_queue.pop(0 )

        if current_node.pos == self.target.pos:
           UpperCamelCase_									=     True
           return self.retrace_path(_UpperCAmelCase )

        UpperCamelCase_									=     self.get_successors(_UpperCAmelCase )

        for node in successors:
           self.node_queue.append(_UpperCAmelCase )

     if not self.reached:
        return [self.start.pos]
     return None




  def    _UpperCAmelCase     (     self		,		_UpperCAmelCase )			-> list[Node]:
     UpperCamelCase_									=     []
     for action in delta:
        UpperCamelCase_									=     parent.pos_x + action[1]
        UpperCamelCase_									=     parent.pos_y + action[0]
        if not (0 <= pos_x <= len(grid[0] ) - 1 and 0 <= pos_y <= len(_UpperCAmelCase ) - 1):
           continue

        if grid[pos_y][pos_x] != 0:
           continue

        successors.append(
            Node(_UpperCAmelCase		,		_UpperCAmelCase		,		self.target.pos_y		,		self.target.pos_x		,		_UpperCAmelCase ) )
     return successors




  def    _UpperCAmelCase     (     self		,		_UpperCAmelCase )			-> Path:
     UpperCamelCase_									=     node
     UpperCamelCase_									=     []
     while current_node is not None:
        path.append((current_node.pos_y, current_node.pos_x) )
        UpperCamelCase_									=     current_node.parent
     path.reverse()
     return path




class 						_a       :






  """simple docstring"""





  def __init__(     self		,		_UpperCAmelCase		,		_UpperCAmelCase )			-> Any:
     UpperCamelCase_									=     BreadthFirstSearch(_UpperCAmelCase		,		_UpperCAmelCase )
     UpperCamelCase_									=     BreadthFirstSearch(_UpperCAmelCase		,		_UpperCAmelCase )
     UpperCamelCase_									=     False




  def    _UpperCAmelCase     (     self )			-> Path | None:
     while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
        UpperCamelCase_									=     self.fwd_bfs.node_queue.pop(0 )
        UpperCamelCase_									=     self.bwd_bfs.node_queue.pop(0 )

        if current_bwd_node.pos == current_fwd_node.pos:
           UpperCamelCase_									=     True
           return self.retrace_bidirectional_path(
               _UpperCAmelCase		,		_UpperCAmelCase )

        UpperCamelCase_									=     current_bwd_node
        UpperCamelCase_									=     current_fwd_node

        UpperCamelCase_									=     {
            self.fwd_bfs: self.fwd_bfs.get_successors(_UpperCAmelCase ),
            self.bwd_bfs: self.bwd_bfs.get_successors(_UpperCAmelCase ),
        }

        for bfs in [self.fwd_bfs, self.bwd_bfs]:
           for node in successors[bfs]:
              bfs.node_queue.append(_UpperCAmelCase )

     if not self.reached:
        return [self.fwd_bfs.start.pos]
     return None




  def    _UpperCAmelCase     (     self		,		_UpperCAmelCase		,		_UpperCAmelCase )			-> Path:
     UpperCamelCase_									=     self.fwd_bfs.retrace_path(_UpperCAmelCase )
     UpperCamelCase_									=     self.bwd_bfs.retrace_path(_UpperCAmelCase )
     bwd_path.pop()
     bwd_path.reverse()
     UpperCamelCase_									=     fwd_path + bwd_path
     return path


if __name__ == "__main__":
 # all coordinates are given in format [y,x]
 import doctest

 doctest.testmod()
 snake_case__      :	Union[str, Any]       	=      (0, 0)
 snake_case__      :	int       	=      (len(grid) - 1, len(grid[0]) - 1)
 for elem in grid:
  print(elem)

 snake_case__      :	Tuple       	=      time.time()
 snake_case__      :	List[Any]       	=      BreadthFirstSearch(init, goal)
 snake_case__      :	Dict       	=      bfs.search()
 snake_case__      :	str       	=      time.time() - start_bfs_time

 print("""Unidirectional BFS computation time : """, bfs_time)

 snake_case__      :	Optional[int]       	=      time.time()
 snake_case__      :	Union[str, Any]       	=      BidirectionalBreadthFirstSearch(init, goal)
 snake_case__      :	Optional[int]       	=      bd_bfs.search()
 snake_case__      :	Optional[Any]       	=      time.time() - start_bd_bfs_time

 print("""Bidirectional BFS computation time : """, bd_bfs_time)













from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
 if not (is_transformers_available() and is_torch_available()):
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 from ...utils.dummy_torch_and_transformers_objects import (
     ImageTextPipelineOutput,
     UniDiffuserPipeline,
 )
else:
 from .modeling_text_decoder import UniDiffuserTextDecoder
 from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
 from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline





