
'''simple docstring'''





import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
						import torch

						from transformers.generation import DisjunctiveConstraint

@require_torch
class 						a   (				unittest.TestCase    ):




				def 	__snake_case							(							self	:				Union[str, Any]      ):
										# For consistency across different places the DisjunctiveConstraint is called,
										# dc.token_ids is a list of integers. It is also initialized only by integers.

										snake_case       :     Optional[Any] =    [[1, 2, 4], [1, 2, 3, 4]]
										snake_case       :     Optional[int] =    DisjunctiveConstraint(SCREAMING_SNAKE_CASE_      )
										self.assertTrue(isinstance(dc.token_ids,    SCREAMING_SNAKE_CASE_      )      )

										with self.assertRaises(SCREAMING_SNAKE_CASE_      ):
																DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]      )      )

										with self.assertRaises(SCREAMING_SNAKE_CASE_      ):
																DisjunctiveConstraint([torch.LongTensor([1, 2, 4]      ), torch.LongTensor([1, 2, 3, 4, 5]      )]      )




				def 	__snake_case							(							self	:				List[str]      ):
										# We can't have constraints that are complete subsets of another. This leads to a preverse
										# interpretation of "constraint fulfillment": does generating [1,2,3] fulfill the constraint?
										# It would mean that it generated [1,2] which fulfills it, but it's in the middle of potentially
										# fulfilling [1,2,3,4]. If we believe that [1,2,3] does fulfill the constraint, then the algorithm
										# will necessarily never reach [1,2,3,4], giving users a false sense of control (better to just not allow it).
										snake_case       :     Optional[Any] =    [[1, 2], [1, 2, 3, 4]]

										with self.assertRaises(SCREAMING_SNAKE_CASE_      ):
																DisjunctiveConstraint(SCREAMING_SNAKE_CASE_      )  # fails here




				def 	__snake_case							(							self	:				Union[str, Any]      ):
										snake_case       :     Union[str, Any] =    [[1, 2, 3], [1, 2, 4]]

										snake_case       :     Optional[Any] =    DisjunctiveConstraint(SCREAMING_SNAKE_CASE_      )

										snake_case,					snake_case,					snake_case       :     Union[str, Any] =    dc.update(1      )
										snake_case       :     Dict =    stepped is True and completed is False and reset is False
										self.assertTrue(SCREAMING_SNAKE_CASE_      )
										self.assertTrue(not dc.completed      )
										self.assertTrue(dc.current_seq == [1]      )

										snake_case,					snake_case,					snake_case       :     List[Any] =    dc.update(2      )
										snake_case       :     Tuple =    stepped is True and completed is False and reset is False
										self.assertTrue(SCREAMING_SNAKE_CASE_      )
										self.assertTrue(not dc.completed      )
										self.assertTrue(dc.current_seq == [1, 2]      )

										snake_case,					snake_case,					snake_case       :     List[Any] =    dc.update(3      )
										snake_case       :     List[str] =    stepped is True and completed is True and reset is False
										self.assertTrue(SCREAMING_SNAKE_CASE_      )
										self.assertTrue(dc.completed      )  # Completed!
										self.assertTrue(dc.current_seq == [1, 2, 3]      )




				def 	__snake_case							(							self	:				Optional[int]      ):
										snake_case       :     List[str] =    [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

										snake_case       :     Union[str, Any] =    DisjunctiveConstraint(SCREAMING_SNAKE_CASE_      )

										snake_case,					snake_case,					snake_case       :     Optional[int] =    dc.update(1      )
										self.assertTrue(not dc.completed      )
										self.assertTrue(dc.current_seq == [1]      )

										snake_case,					snake_case,					snake_case       :     Tuple =    dc.update(2      )
										self.assertTrue(not dc.completed      )
										self.assertTrue(dc.current_seq == [1, 2]      )

										snake_case,					snake_case,					snake_case       :     Optional[int] =    dc.update(4      )
										self.assertTrue(not dc.completed      )
										self.assertTrue(dc.current_seq == [1, 2, 4]      )

										snake_case,					snake_case,					snake_case       :     List[Any] =    dc.update(5      )
										self.assertTrue(dc.completed      )  # Completed!
										self.assertTrue(dc.current_seq == [1, 2, 4, 5]      )

										dc.reset()

										snake_case,					snake_case,					snake_case       :     Dict =    dc.update(1      )
										self.assertTrue(not dc.completed      )
										self.assertTrue(dc.remaining() == 3      )
										self.assertTrue(dc.current_seq == [1]      )

										snake_case,					snake_case,					snake_case       :     Optional[Any] =    dc.update(2      )
										self.assertTrue(not dc.completed      )
										self.assertTrue(dc.remaining() == 2      )
										self.assertTrue(dc.current_seq == [1, 2]      )

										snake_case,					snake_case,					snake_case       :     str =    dc.update(5      )
										self.assertTrue(dc.completed      )  # Completed!
										self.assertTrue(dc.remaining() == 0      )
										self.assertTrue(dc.current_seq == [1, 2, 5]      )



'''simple docstring'''





import numpy as np

class 						a   :




				def __init__(							self	:				Dict      ):
										snake_case       :     List[str] =    (0, 0)
										snake_case       :     Tuple =    None
										snake_case       :     Union[str, Any] =    0
										snake_case       :     Dict =    0
										snake_case       :     List[str] =    0




				def __eq__(							self	:				str,    SCREAMING_SNAKE_CASE_	:				List[Any]      ):
										return self.position == cell.position




				def 	__snake_case							(							self	:				Optional[int]      ):
										print(self.position      )




class 						a   :




				def __init__(							self	:				Dict,    SCREAMING_SNAKE_CASE_	:				Union[str, Any]=(5, 5)      ):
										snake_case       :     int =    np.zeros(SCREAMING_SNAKE_CASE_      )
										snake_case       :     Optional[int] =    world_size[0]
										snake_case       :     Optional[Any] =    world_size[1]




				def 	__snake_case							(							self	:				Any      ):
										print(self.w      )




				def 	__snake_case							(							self	:				str,    SCREAMING_SNAKE_CASE_	:				Optional[int]      ):
										snake_case       :     Union[str, Any] =    [
										    (-1, -1),
										    (-1, 0),
										    (-1, 1),
										    (0, -1),
										    (0, 1),
										    (1, -1),
										    (1, 0),
										    (1, 1),
										]
										snake_case       :     str =    cell.position[0]
										snake_case       :     Optional[Any] =    cell.position[1]
										snake_case       :     Any =    []
										for n in neughbour_cord:
																snake_case       :     List[str] =    current_x + n[0]
																snake_case       :     Tuple =    current_y + n[1]
																if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																						snake_case       :     int =    Cell()
																						snake_case       :     int =    (x, y)
																						snake_case       :     Any =    cell
																						neighbours.append(SCREAMING_SNAKE_CASE_      )
										return neighbours




def      A (       A_							:					Tuple    ,							A_							:					Tuple    ,							A_							:					Union[str, Any]       ):
						snake_case       :     Union[str, Any] =    []
						snake_case       :     Union[str, Any] =    []
						_open.append(A_       )

						while _open:
												snake_case       :     List[Any] =    np.argmin([n.f for n in _open]       )
												snake_case       :     List[Any] =    _open[min_f]
												_closed.append(_open.pop(A_       )       )
												if current == goal:
																		break
												for n in world.get_neigbours(A_       ):
																		for c in _closed:
																								if c == n:
																														continue
																		snake_case       :     Dict =    current.g + 1
																		snake_case,					snake_case       :     Optional[Any] =    n.position
																		snake_case,					snake_case       :     Union[str, Any] =    goal.position
																		snake_case       :     Tuple =    (ya - ya) ** 2 + (xa - xa) ** 2
																		snake_case       :     Union[str, Any] =    n.h + n.g

																		for c in _open:
																								if c == n and c.f < n.f:
																														continue
																		_open.append(A_       )
						snake_case       :     Dict =    []
						while current.parent is not None:
												path.append(current.position       )
												snake_case       :     Tuple =    current.parent
						path.append(current.position       )
						return path[::-1]


if __name__ == "__main__":
						UpperCAmelCase    					=   Gridworld()
						# Start position and goal
						UpperCAmelCase    					=   Cell()
						UpperCAmelCase    					=   (0, 0)
						UpperCAmelCase    					=   Cell()
						UpperCAmelCase    					=   (4, 4)
						print(f'''path from {start.position} to {goal.position}''')
						UpperCAmelCase    					=   astar(world, start, goal)
						#   Just for visual reasons.
						for i in s:
												UpperCAmelCase    					=   1
						print(world.w)

