



import math



class _A  :





		def __init__(     self ,       __UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase				)       ->     List[Any]:

					'''simple docstring'''
					__UpperCAmelCase   :      int										=     x
					__UpperCAmelCase   :      int										=     y
					__UpperCAmelCase   :      Union[str, Any]										=     step_size
					__UpperCAmelCase   :      Optional[Any]										=     function_to_optimize





		def 							__A       (     self				)       ->     int:

					'''simple docstring'''
					return self.function(self.x ,       self.y				)





		def 							__A       (     self				)       ->     List[str]:

					'''simple docstring'''
					__UpperCAmelCase   :      Dict										=     self.step_size
					return [
					    SearchProblem(__UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase ,       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				)       ->     Tuple:

					'''simple docstring'''
					return hash(str(self				)				)





		def __eq__(     self ,       __UpperCAmelCase				)       ->     Dict:

					'''simple docstring'''
					if isinstance(__UpperCAmelCase ,       __UpperCAmelCase				):
								return hash(str(self				)				) == hash(str(__UpperCAmelCase				)				)
					return False





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

					'''simple docstring'''
					return f'x: {self.x} y: {self.y}'


def   lowercase_	(   lowerCAmelCase__	:  Any			,							lowerCAmelCase__	:  bool = True			,							lowerCAmelCase__	:  float = math.inf			,							lowerCAmelCase__	:  float = -math.inf			,							lowerCAmelCase__	:  float = math.inf			,							lowerCAmelCase__	:  float = -math.inf			,							lowerCAmelCase__	:  bool = False			,							lowerCAmelCase__	:  int = 10000			,							):

			"""simple docstring"""





			__UpperCAmelCase   :      Tuple										=     search_prob
			__UpperCAmelCase   :      Any										=     []  # list to store the current score at each iteration
			__UpperCAmelCase   :      Dict										=     0
			__UpperCAmelCase   :      str										=     False
			__UpperCAmelCase   :      Dict										=     set()
			while not solution_found and iterations < max_iter:
						visited.add(lowerCAmelCase__ )
						iterations += 1
						__UpperCAmelCase   :      Optional[int]										=     current_state.score()
						scores.append(lowerCAmelCase__ )
						__UpperCAmelCase   :      str										=     current_state.get_neighbors()
						__UpperCAmelCase   :      Optional[int]										=     -math.inf
						__UpperCAmelCase   :      Optional[Any]										=     math.inf
						__UpperCAmelCase   :      Union[str, 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
									__UpperCAmelCase   :      Optional[int]										=     neighbor.score() - current_score
									if find_max:  # finding max
												# going to direction with greatest ascent
												if change > max_change and change > 0:
															__UpperCAmelCase   :      str										=     change
															__UpperCAmelCase   :      Tuple										=     neighbor
									else:  # finding min
												# to direction with greatest descent
												if change < min_change and change < 0:
															__UpperCAmelCase   :      List[str]										=     change
															__UpperCAmelCase   :      List[Any]										=     neighbor
						if next_state is not None:
									# we found at least one neighbor which improved the current state
									__UpperCAmelCase   :      Optional[int]										=     next_state
						else:
									# since we have no neighbor that improves the solution we stop the search
									__UpperCAmelCase   :      Dict										=     True

			if visualization:
						from matplotlib import pyplot as plt

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

			return current_state


if __name__ == "__main__":
					import doctest

					doctest.testmod()


					def   lowercase_	(   lowerCAmelCase__	:  Tuple			,							lowerCAmelCase__	:  List[Any] ):

								"""simple docstring"""





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

					# starting the problem with initial coordinates (3, 4)
					_UpperCamelCase											=			SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
					_UpperCamelCase											=			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)
					_UpperCamelCase											=			SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
					_UpperCamelCase											=			hill_climbing(
					    prob, find_max=False, max_x=100, 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   lowercase_	(   lowerCAmelCase__	:  Any			,							lowerCAmelCase__	:  Union[str, Any] ):

								"""simple docstring"""





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

					_UpperCamelCase											=			SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
					_UpperCamelCase											=			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()}'
					)









'''simple docstring'''
import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


_UpperCamelCase											=			logging.get_logger(__name__)



class _A  (    __SCREAMING_SNAKE_CASE    ):





		def __init__(     self ,       *__UpperCAmelCase ,       **__UpperCAmelCase				)       ->     None:

					'''simple docstring'''
					warnings.warn(
					    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
					    """ Please use MobileNetV2ImageProcessor instead.""" ,       __UpperCAmelCase ,       )
					super().__init__(*__UpperCAmelCase ,       **__UpperCAmelCase				)




