

import math






class 			__magic_name__					:





			def __init__(	self      ,						__snake_case      ,						__snake_case      ,						__snake_case      ,						__snake_case      )     ->				str:




						'''simple docstring'''
						__a						   =x
						__a						   =y
						__a						   =step_size
						__a						   =function_to_optimize





			def 	__magic_name__					(	self      )     ->				int:




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





			def 	__magic_name__					(	self      )     ->				Dict:




						'''simple docstring'''
						__a						   =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      )     ->				Optional[Any]:




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





			def __eq__(	self      ,						__snake_case      )     ->				str:




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





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




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






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




			"""simple docstring"""






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

			if visualization:
						from matplotlib import pyplot as plt

						plt.plot(range(_snake_case			) ,  _snake_case			)
						plt.xlabel('Iterations'			)
						plt.ylabel('Function values'			)
						plt.show()

			return current_state


if __name__ == "__main__":
						import doctest

						doctest.testmod()






						def  UpperCamelCase_(							_snake_case     :						Union[str, Any] ,  _snake_case     :						Optional[Any]			):




									"""simple docstring"""






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

						# starting the problem with initial coordinates (3, 4)
						_lowerCAmelCase      :    Dict						       =    SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
						_lowerCAmelCase      :    Optional[Any]						       =    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      :    List[Any]						       =    SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
						_lowerCAmelCase      :    Optional[Any]						       =    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_(							_snake_case     :						str ,  _snake_case     :						Union[str, Any]			):




									"""simple docstring"""






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

						_lowerCAmelCase      :    Union[str, Any]						       =    SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
						_lowerCAmelCase      :    Union[str, Any]						       =    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

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


_lowerCAmelCase      :    Union[str, Any]						       =    {
    "configuration_ernie_m": ["ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieMConfig"],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase      :    str						       =    ["ErnieMTokenizer"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowerCAmelCase      :    Optional[Any]						       =    [
						    "ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "ErnieMForMultipleChoice",
						    "ErnieMForQuestionAnswering",
						    "ErnieMForSequenceClassification",
						    "ErnieMForTokenClassification",
						    "ErnieMModel",
						    "ErnieMPreTrainedModel",
						    "ErnieMForInformationExtraction",
						]


if TYPE_CHECKING:
						from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_ernie_m import ErnieMTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_ernie_m import (
												    ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ErnieMForInformationExtraction,
												    ErnieMForMultipleChoice,
												    ErnieMForQuestionAnswering,
												    ErnieMForSequenceClassification,
												    ErnieMForTokenClassification,
												    ErnieMModel,
												    ErnieMPreTrainedModel,
												)


else:
						import sys

						_lowerCAmelCase      :    Tuple						       =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






