

import math







class  __lowerCamelCase				:







      def __init__(     self							,  lowerCamelCase							,  lowerCamelCase							,  lowerCamelCase							,  lowerCamelCase   )						->       str:
        snake_case_       						=      x
        snake_case_       						=      y
        snake_case_       						=      step_size
        snake_case_       						=      function_to_optimize







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







      def 	lowerCAmelCase_    (     self   )						->       str:
        snake_case_       						=      self.step_size
        return [
            SearchProblem(lowerCamelCase							,  lowerCamelCase							,  lowerCamelCase							,  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   )						->       List[Any]:
        return hash(str(self   )   )







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







      def __str__(     self   )						->       Dict:
        return f'''x: {self.x} y: {self.y}'''



def    UpperCamelCase(					lowercase_			,					lowercase_ = True			,					lowercase_ = math.inf			,					lowercase_ = -math.inf			,					lowercase_ = math.inf			,					lowercase_ = -math.inf			,					lowercase_ = False			,					lowercase_ = 10000			,					)	->				SearchProblem:





  '''simple docstring'''





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





      '''simple docstring'''





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

    # starting the problem with initial coordinates (3, 4)
    lowerCamelCase_    =					SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
    lowerCamelCase_    =					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)
    lowerCamelCase_    =					SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
    lowerCamelCase_    =					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    UpperCamelCase(					lowercase_			,					lowercase_							)	->				List[str]:





      '''simple docstring'''





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

    lowerCamelCase_    =					SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
    lowerCamelCase_    =					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()}"""
    )

import warnings

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


lowerCamelCase_  :       List[Any]					      =     logging.get_logger(__name__)

class 				_UpperCamelCase (    _A     ):






			'''simple docstring'''

			def __init__(				self       :				Dict  ,		*snake_case_       :				Optional[int]  ,		**snake_case_       :				List[Any]					):
							warnings.warn(
							    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
							    """ Please use MobileNetV2ImageProcessor instead."""  ,		snake_case_  ,		)
							super().__init__(*snake_case_  ,		**snake_case_					)






