





'''simple docstring'''






from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
snake_case_     =	0

snake_case_     =	[
    [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_     =	[[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

snake_case_     =	tuple[int, int]


class   _lowercase						:


   def __init__( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase    ,   _UpperCAmelCase    ,   _UpperCAmelCase    ,   _UpperCAmelCase    ,   _UpperCAmelCase    ,   ):
       A       :       Union[str, Any]							=						pos_x
       A       :       Dict							=						pos_y
       A       :       Tuple							=						(pos_y, pos_x)
       A       :       Dict							=						goal_x
       A       :       List[Any]							=						goal_y
       A       :       Dict							=						g_cost
       A       :       Optional[int]							=						parent
       A       :       Optional[int]							=						self.calculate_heuristic()
       A       :       Optional[int]							=						self.g_cost + self.h_cost


   def 					snake_case				( self					):
       A       :       Dict							=						self.pos_x - self.goal_x
       A       :       Dict							=						self.pos_y - self.goal_y
       if HEURISTIC == 1:
           return abs(lowerCAmelCase_					) + abs(lowerCAmelCase_					)
       else:
           return sqrt(dy**2 + dx**2					)


   def __lt__( self    ,   _UpperCAmelCase					):
       return self.f_cost < other.f_cost







class   _lowercase						:


   def __init__( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase					):
       A       :       int							=						Node(start[1]    ,   start[0]    ,   goal[1]    ,   goal[0]    ,   0    ,   lowerCAmelCase_					)
       A       :       Dict							=						Node(goal[1]    ,   goal[0]    ,   goal[1]    ,   goal[0]    ,   99_999    ,   lowerCAmelCase_					)

       A       :       Optional[Any]							=						[self.start]
       A       :       List[Any]							=						[]

       A       :       str							=						False


   def 					snake_case				( self					):







       while self.open_nodes:
           # Open Nodes are sorted using __lt__
           self.open_nodes.sort()
           A       :       List[Any]							=						self.open_nodes.pop(0					)

           if current_node.pos == self.target.pos:
               return self.retrace_path(lowerCAmelCase_					)

           self.closed_nodes.append(lowerCAmelCase_					)
           A       :       Optional[Any]							=						self.get_successors(lowerCAmelCase_					)

           for child_node in successors:
               if child_node in self.closed_nodes:
                   continue

               if child_node not in self.open_nodes:
                   self.open_nodes.append(lowerCAmelCase_					)
               else:
                   # retrieve the best current path
                   A       :       Optional[Any]							=						self.open_nodes.pop(self.open_nodes.index(lowerCAmelCase_					)					)

                   if child_node.g_cost < better_node.g_cost:
                       self.open_nodes.append(lowerCAmelCase_					)
                   else:
                       self.open_nodes.append(lowerCAmelCase_					)

       return [self.start.pos]


   def 					snake_case				( self    ,   _UpperCAmelCase					):
       A       :       str							=						[]
       for action in delta:
           A       :       List[Any]							=						parent.pos_x + action[1]
           A       :       Optional[int]							=						parent.pos_y + action[0]
           if not (0 <= pos_x <= len(grid[0]					) - 1 and 0 <= pos_y <= len(lowerCAmelCase_					) - 1):
               continue

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

           successors.append(
               Node(
                   lowerCAmelCase_    ,   lowerCAmelCase_    ,   self.target.pos_y    ,   self.target.pos_x    ,   parent.g_cost + 1    ,   lowerCAmelCase_    ,   )					)
       return successors


   def 					snake_case				( self    ,   _UpperCAmelCase					):
       A       :       Optional[int]							=						node
       A       :       Any							=						[]
       while current_node is not None:
           path.append((current_node.pos_y, current_node.pos_x)					)
           A       :       List[str]							=						current_node.parent
       path.reverse()
       return path







class   _lowercase						:


   def __init__( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase					):
       A       :       Optional[int]							=						AStar(lowerCAmelCase_    ,   lowerCAmelCase_					)
       A       :       str							=						AStar(lowerCAmelCase_    ,   lowerCAmelCase_					)
       A       :       str							=						False


   def 					snake_case				( self					):







       while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
           self.fwd_astar.open_nodes.sort()
           self.bwd_astar.open_nodes.sort()
           A       :       Any							=						self.fwd_astar.open_nodes.pop(0					)
           A       :       Any							=						self.bwd_astar.open_nodes.pop(0					)

           if current_bwd_node.pos == current_fwd_node.pos:
               return self.retrace_bidirectional_path(
                   lowerCAmelCase_    ,   lowerCAmelCase_					)

           self.fwd_astar.closed_nodes.append(lowerCAmelCase_					)
           self.bwd_astar.closed_nodes.append(lowerCAmelCase_					)

           A       :       Optional[Any]							=						current_bwd_node
           A       :       Dict							=						current_fwd_node

           A       :       Tuple							=						{
               self.fwd_astar: self.fwd_astar.get_successors(lowerCAmelCase_					),
               self.bwd_astar: self.bwd_astar.get_successors(lowerCAmelCase_					),
           }

           for astar in [self.fwd_astar, self.bwd_astar]:
               for child_node in successors[astar]:
                   if child_node in astar.closed_nodes:
                       continue

                   if child_node not in astar.open_nodes:
                       astar.open_nodes.append(lowerCAmelCase_					)
                   else:
                       # retrieve the best current path
                       A       :       Union[str, Any]							=						astar.open_nodes.pop(
                           astar.open_nodes.index(lowerCAmelCase_					)					)

                       if child_node.g_cost < better_node.g_cost:
                           astar.open_nodes.append(lowerCAmelCase_					)
                       else:
                           astar.open_nodes.append(lowerCAmelCase_					)

       return [self.fwd_astar.start.pos]


   def 					snake_case				( self    ,   _UpperCAmelCase    ,   _UpperCAmelCase					):
       A       :       Union[str, Any]							=						self.fwd_astar.retrace_path(lowerCAmelCase_					)
       A       :       Dict							=						self.bwd_astar.retrace_path(lowerCAmelCase_					)
       bwd_path.pop()
       bwd_path.reverse()
       A       :       str							=						fwd_path + bwd_path
       return path


if __name__ == "__main__":
     # all coordinates are given in format [y,x]
     snake_case_     =	(0, 0)
     snake_case_     =	(len(grid) - 1, len(grid[0]) - 1)
     for elem in grid:
          print(elem)

     snake_case_     =	time.time()
     snake_case_     =	AStar(init, goal)
     snake_case_     =	a_star.search()
     snake_case_     =	time.time() - start_time
     print(f'''AStar execution time = {end_time:f} seconds''')

     snake_case_     =	time.time()
     snake_case_     =	BidirectionalAStar(init, goal)
     snake_case_     =	time.time() - bd_start_time
     print(f'''BidirectionalAStar execution time = {bd_end_time:f} seconds''')







'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


snake_case_     =	{
    """configuration_speecht5""": [
        """SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP""",
        """SpeechT5Config""",
        """SpeechT5HifiGanConfig""",
    ],
    """feature_extraction_speecht5""": ["""SpeechT5FeatureExtractor"""],
    """processing_speecht5""": ["""SpeechT5Processor"""],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case_     =	["""SpeechT5Tokenizer"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case_     =	[
         """SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """SpeechT5ForSpeechToText""",
         """SpeechT5ForSpeechToSpeech""",
         """SpeechT5ForTextToSpeech""",
         """SpeechT5Model""",
         """SpeechT5PreTrainedModel""",
         """SpeechT5HifiGan""",
     ]

if TYPE_CHECKING:
     from .configuration_speechta import (
         SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
         SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
         SpeechTaConfig,
         SpeechTaHifiGanConfig,
     )
     from .feature_extraction_speechta import SpeechTaFeatureExtractor
     from .processing_speechta import SpeechTaProcessor

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_speechta import SpeechTaTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_speechta import (
              SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
              SpeechTaForSpeechToSpeech,
              SpeechTaForSpeechToText,
              SpeechTaForTextToSpeech,
              SpeechTaHifiGan,
              SpeechTaModel,
              SpeechTaPreTrainedModel,
          )

else:
     import sys

     snake_case_     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
