



"""simple docstring"""
import math
class 							lowerCamelCase    :






					'''simple docstring'''





					def __init__(			self:				Optional[int]		,	snake_case:				int		,	snake_case:				int		,	snake_case:				int		,	snake_case:				Union[str, Any]		)  ->      str:
											snake_case_					:Tuple		=     x
											snake_case_					:List[Any]		=     y
											snake_case_					:Any		=     step_size
											snake_case_					:Tuple		=     function_to_optimize






					def   lowerCAmelCase_							(			self:				Tuple		)  ->      int:
											return self.function(self.x		,	self.y		)






					def   lowerCAmelCase_							(			self:				Optional[int]		)  ->      Optional[int]:
											snake_case_					:Tuple		=     self.step_size
											return [
											    SearchProblem(snake_case		,	snake_case		,	snake_case		,	self.function		)
											    for x, y in (
											        (self.x - step_size, self.y - step_size),
											        (self.x - step_size, self.y),
											        (self.x - step_size, self.y + step_size),
											        (self.x, self.y - step_size),
											        (self.x, self.y + step_size),
											        (self.x + step_size, self.y - step_size),
											        (self.x + step_size, self.y),
											        (self.x + step_size, self.y + step_size),
											    )
											]






					def __hash__(			self:				str		)  ->      Tuple:
											return hash(str(self		)		)






					def __eq__(			self:				Tuple		,	snake_case:				List[str]		)  ->      Optional[int]:
											if isinstance(snake_case		,	snake_case		):
																	return hash(str(self		)		) == hash(str(snake_case		)		)
											return False






					def __str__(			self:				Tuple		)  ->      str:
											return f"""x: {self.x} y: {self.y}"""

def   A_    (     _lowercase,   _lowercase = True,   _lowercase = math.inf,   _lowercase = -math.inf,   _lowercase = math.inf,   _lowercase = -math.inf,   _lowercase = False,   _lowercase = 10000,   ):







						'''simple docstring'''


						snake_case_					:Tuple		=     search_prob
						snake_case_					:int		=     []  # list to store the current score at each iteration
						snake_case_					:Union[str, Any]		=     0
						snake_case_					:Optional[Any]		=     False
						snake_case_					:str		=     set()
						while not solution_found and iterations < max_iter:
												visited.add(_lowercase      )
												iterations += 1
												snake_case_					:Dict		=     current_state.score()
												scores.append(_lowercase      )
												snake_case_					:Any		=     current_state.get_neighbors()
												snake_case_					:Optional[int]		=     -math.inf
												snake_case_					:List[str]		=     math.inf
												snake_case_					:Any		=     None  # to hold the next best neighbor
												for neighbor in neighbors:
																		if neighbor in visited:
																								continue  # do not want to visit the same state again
																		if (
																		    neighbor.x > max_x
																		    or neighbor.x < min_x
																		    or neighbor.y > max_y
																		    or neighbor.y < min_y
																		):
																								continue  # neighbor outside our bounds
																		snake_case_					:List[str]		=     neighbor.score() - current_score
																		if find_max:  # finding max
																								# going to direction with greatest ascent
																								if change > max_change and change > 0:
																														snake_case_					:int		=     change
																														snake_case_					:Optional[int]		=     neighbor
																		else:  # finding min
																								# to direction with greatest descent
																								if change < min_change and change < 0:
																														snake_case_					:Any		=     change
																														snake_case_					:Optional[int]		=     neighbor
												if next_state is not None:
																		# we found at least one neighbor which improved the current state
																		snake_case_					:Tuple		=     next_state
												else:
																		# since we have no neighbor that improves the solution we stop the search
																		snake_case_					:Union[str, Any]		=     True

						if visualization:
												from matplotlib import pyplot as plt

												plt.plot(range(_lowercase      ),   _lowercase      )
												plt.xlabel("""Iterations"""      )
												plt.ylabel("""Function values"""      )
												plt.show()

						return current_state


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						def   A_    (     _lowercase,   _lowercase      ):







												'''simple docstring'''


												return (x**2) + (y**2)

						# starting the problem with initial coordinates (3, 4)
						__a           =							SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
						__a           =							hill_climbing(prob, find_max=False)
						print(
						    "The minimum score for f(x, y) = x^2 + y^2 found via hill climbing: "
						    F"""{local_min.score()}"""
						)

						# starting the problem with initial coordinates (12, 47)
						__a           =							SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
						__a           =							hill_climbing(
						    prob, find_max=False, max_x=1_00, min_x=5, max_y=50, min_y=-5, visualization=True
						)
						print(
						    "The minimum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 "
						    F"""and 50 > y > - 5 found via hill climbing: {local_min.score()}"""
						)
						def   A_    (     _lowercase,   _lowercase      ):







												'''simple docstring'''


												return (3 * x**2) - (6 * y)

						__a           =							SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
						__a           =							hill_climbing(prob, find_max=True)

						print(
						    "The maximum score for f(x, y) = x^2 + y^2 found via hill climbing: "
						    F"""{local_min.score()}"""
						)




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__SCREAMING_SNAKE_CASE	:							Optional[int]           =  {'''configuration_sew_d''': ['''SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWDConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE	:							Dict           =  [
		    '''SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''SEWDForCTC''',
		    '''SEWDForSequenceClassification''',
		    '''SEWDModel''',
		    '''SEWDPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_sew_d import (
				    SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
				    SEWDForCTC,
				    SEWDForSequenceClassification,
				    SEWDModel,
				    SEWDPreTrainedModel,
				)


else:
		import sys

		__SCREAMING_SNAKE_CASE	:							Tuple           =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

