



"""simple docstring"""






import time
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device

from ..test_modeling_common import ids_tensor


if is_torch_available():
	import torch

	from transformers.generation import (
	    MaxLengthCriteria,
	    MaxNewTokensCriteria,
	    MaxTimeCriteria,
	    StoppingCriteriaList,
	    validate_stopping_criteria,
	)



@require_torch
class      A__  (    unittest.TestCase				):




	'''simple docstring'''





	def 				_SCREAMING_SNAKE_CASE  (	self:						Any			,     _SCREAMING_SNAKE_CASE:						Any)							->			Union[str, Any]:

				"""simple docstring"""

				__lowerCAmelCase :    Dict				=			3
				__lowerCAmelCase :    Tuple				=			250

				__lowerCAmelCase :    Optional[Any]				=			ids_tensor((batch_size, length)			,     A_)
				__lowerCAmelCase :    Any				=			torch.ones((batch_size, length)			,     device=A_			,     dtype=torch.float) / length
				return input_ids, scores

	def 				_SCREAMING_SNAKE_CASE  (	self:						List[str])							->			List[Any]:

				"""simple docstring"""

				__lowerCAmelCase		,      __lowerCAmelCase :    Optional[int]				=			self._get_tensors(5)

				__lowerCAmelCase :    Optional[int]				=			StoppingCriteriaList(
				    [
				        MaxLengthCriteria(max_length=10),
				        MaxTimeCriteria(max_time=0.1),
				    ])

				self.assertFalse(criteria(A_			,     A_))

				__lowerCAmelCase		,      __lowerCAmelCase :    List[Any]				=			self._get_tensors(9)
				self.assertFalse(criteria(A_			,     A_))

				__lowerCAmelCase		,      __lowerCAmelCase :    List[Any]				=			self._get_tensors(10)
				self.assertTrue(criteria(A_			,     A_))

	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[int])							->			Optional[int]:

				"""simple docstring"""

				__lowerCAmelCase :    Any				=			MaxLengthCriteria(max_length=10)

				__lowerCAmelCase		,      __lowerCAmelCase :    int				=			self._get_tensors(5)
				self.assertFalse(criteria(A_			,     A_))

				__lowerCAmelCase		,      __lowerCAmelCase :    List[Any]				=			self._get_tensors(9)
				self.assertFalse(criteria(A_			,     A_))

				__lowerCAmelCase		,      __lowerCAmelCase :    List[Any]				=			self._get_tensors(10)
				self.assertTrue(criteria(A_			,     A_))

	def 				_SCREAMING_SNAKE_CASE  (	self:						List[str])							->			Dict:

				"""simple docstring"""

				__lowerCAmelCase :    Optional[Any]				=			MaxNewTokensCriteria(start_length=5			,     max_new_tokens=5)

				__lowerCAmelCase		,      __lowerCAmelCase :    Dict				=			self._get_tensors(5)
				self.assertFalse(criteria(A_			,     A_))

				__lowerCAmelCase		,      __lowerCAmelCase :    Dict				=			self._get_tensors(9)
				self.assertFalse(criteria(A_			,     A_))

				__lowerCAmelCase		,      __lowerCAmelCase :    List[Any]				=			self._get_tensors(10)
				self.assertTrue(criteria(A_			,     A_))

				__lowerCAmelCase :    Any				=			StoppingCriteriaList([criteria])
				self.assertEqual(criteria_list.max_length			,     10)

	def 				_SCREAMING_SNAKE_CASE  (	self:						Dict)							->			int:

				"""simple docstring"""

				__lowerCAmelCase		,      __lowerCAmelCase :    Any				=			self._get_tensors(5)

				__lowerCAmelCase :    List[str]				=			MaxTimeCriteria(max_time=0.1)
				self.assertFalse(criteria(A_			,     A_))

				__lowerCAmelCase :    Optional[int]				=			MaxTimeCriteria(max_time=0.1			,     initial_timestamp=time.time() - 0.2)
				self.assertTrue(criteria(A_			,     A_))







	def 				_SCREAMING_SNAKE_CASE  (	self:						Optional[Any])							->			Dict:

				"""simple docstring"""

				validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10)])			,     10)

				with self.assertWarns(A_):
							validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10)])			,     11)

				__lowerCAmelCase :    Tuple				=			validate_stopping_criteria(StoppingCriteriaList()			,     11)

				self.assertEqual(len(A_)			,     1)



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 	__lowerCamelCase			:







       def __init__(			self: str,A_: int,A_: int,A_: int,A_: int,A_: int,A_: Node | None,):






            '''simple docstring'''




            __UpperCamelCase =			pos_x
            __UpperCamelCase =			pos_y
            __UpperCamelCase =			(pos_y, pos_x)
            __UpperCamelCase =			goal_x
            __UpperCamelCase =			goal_y
            __UpperCamelCase =			g_cost
            __UpperCamelCase =			parent
            __UpperCamelCase =			self.calculate_heuristic()
            __UpperCamelCase =			self.g_cost + self.h_cost







       def 		snake_case_	(			self: str					):






            '''simple docstring'''




            __UpperCamelCase =			self.pos_x - self.goal_x
            __UpperCamelCase =			self.pos_y - self.goal_y
            if HEURISTIC == 1:
                 return abs(A_					) + abs(A_					)
            else:
                 return sqrt(dy**2 + dx**2					)







       def __lt__(			self: int,A_: Node					):






            '''simple docstring'''




            return self.f_cost < other.f_cost



class 	__lowerCamelCase			:







       def __init__(			self: Any,A_: TPosition,A_: TPosition					):






            '''simple docstring'''




            __UpperCamelCase =			Node(start[1],start[0],goal[1],goal[0],0,A_					)
            __UpperCamelCase =			Node(goal[1],goal[0],goal[1],goal[0],9_9999,A_					)

            __UpperCamelCase =			[self.start]
            __UpperCamelCase =			[]

            __UpperCamelCase =			False







       def 		snake_case_	(			self: Any					):






            '''simple docstring'''




            while self.open_nodes:
                 # Open Nodes are sorted using __lt__
                 self.open_nodes.sort()
                 __UpperCamelCase =			self.open_nodes.pop(0					)

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

                 self.closed_nodes.append(A_					)
                 __UpperCamelCase =			self.get_successors(A_					)

                 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(A_					)
                      else:
                           # retrieve the best current path
                           __UpperCamelCase =			self.open_nodes.pop(self.open_nodes.index(A_					)					)

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

            return [self.start.pos]







       def 		snake_case_	(			self: int,A_: Node					):






            '''simple docstring'''




            __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(A_					) - 1):
                      continue

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

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







       def 		snake_case_	(			self: Any,A_: Node | None					):






            '''simple docstring'''




            __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 	__lowerCamelCase			:







       def __init__(			self: List[Any],A_: TPosition,A_: TPosition					):






            '''simple docstring'''




            __UpperCamelCase =			AStar(A_,A_					)
            __UpperCamelCase =			AStar(A_,A_					)
            __UpperCamelCase =			False







       def 		snake_case_	(			self: Union[str, Any]					):






            '''simple docstring'''




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

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

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

                 __UpperCamelCase =			current_bwd_node
                 __UpperCamelCase =			current_fwd_node

                 __UpperCamelCase =			{
                     self.fwd_astar: self.fwd_astar.get_successors(A_					),
                     self.bwd_astar: self.bwd_astar.get_successors(A_					),
                 }

                 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(A_					)
                           else:
                                # retrieve the best current path
                                __UpperCamelCase =			astar.open_nodes.pop(
                                    astar.open_nodes.index(A_					)					)

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

            return [self.fwd_astar.start.pos]







       def 		snake_case_	(			self: List[str],A_: Node,A_: Node					):






            '''simple docstring'''




            __UpperCamelCase =			self.fwd_astar.retrace_path(A_					)
            __UpperCamelCase =			self.bwd_astar.retrace_path(A_					)
            bwd_path.pop()
            bwd_path.reverse()
            __UpperCamelCase =			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""")


