code: 
  
  
  
  
  
  
  import math
  
  class 					snake_case_							:
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
     def __init__(    self:	Optional[int]   ,       snake_case__:	Union[str, Any]   ,       snake_case__:	Any   ,       snake_case__:	Optional[int]   ,       snake_case__:	List[str]	)  ->		Any:
  
  
         """simple docstring"""
  
  
  
         _lowercase     =	x
         _lowercase     =	y
         _lowercase     =	step_size
         _lowercase     =	function_to_optimize
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	str	)  ->		int:
  
  
         """simple docstring"""
  
  
  
         return self.function(self.x   ,       self.y	)
  
     def 			SCREAMING_SNAKE_CASE__				(    self:	List[Any]	)  ->		Dict:
  
  
         """simple docstring"""
  
  
  
         _lowercase     =	self.step_size
         return [
             SearchProblem(a_   ,       a_   ,       a_   ,       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[str]	)  ->		List[Any]:
  
  
         """simple docstring"""
  
  
  
         return hash(str(self	)	)
  
     def __eq__(    self:	Any   ,       snake_case__:	Any	)  ->		Optional[Any]:
  
  
         """simple docstring"""
  
  
  
         if isinstance(a_   ,       a_	):
             return hash(str(self	)	) == hash(str(a_	)	)
         return False
  
     def __str__(    self:	Union[str, Any]	)  ->		List[Any]:
  
  
         """simple docstring"""
  
  
  
         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,      ):
  
  
      '''simple docstring'''
  
  
  
      _lowercase     =	search_prob
      _lowercase     =	[]  # list to store the current score at each iteration
      _lowercase     =	0
      _lowercase     =	False
      _lowercase     =	set()
      while not solution_found and iterations < max_iter:
          visited.add(UpperCamelCase__      )
          iterations += 1
          _lowercase     =	current_state.score()
          scores.append(UpperCamelCase__      )
          _lowercase     =	current_state.get_neighbors()
          _lowercase     =	-math.inf
          _lowercase     =	math.inf
          _lowercase     =	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
              _lowercase     =	neighbor.score() - current_score
              if find_max:  # finding max
                  # going to direction with greatest ascent
                  if change > max_change and change > 0:
                      _lowercase     =	change
                      _lowercase     =	neighbor
              else:  # finding min
                  # to direction with greatest descent
                  if change < min_change and change < 0:
                      _lowercase     =	change
                      _lowercase     =	neighbor
          if next_state is not None:
              # we found at least one neighbor which improved the current state
              _lowercase     =	next_state
          else:
              # since we have no neighbor that improves the solution we stop the search
              _lowercase     =	True
  
      if visualization:
          from matplotlib import pyplot as plt
  
          plt.plot(range(UpperCamelCase__      ),      UpperCamelCase__      )
          plt.xlabel('Iterations'      )
          plt.ylabel('Function values'      )
          plt.show()
  
      return current_state
  
  
  if __name__ == "__main__":
     import doctest
  
     doctest.testmod()
     def        UpperCAmelCase      (   _lowercase,      _lowercase      ):
  
  
         '''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      ):
  
  
         '''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()}"
     )
  
  
  
  
style_context: 
  
  
  
  
  
  
  from typing import List, Union
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowerCamelCase										=  logging.get_logger(__name__)
  
  lowerCamelCase										=  {
      '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/config.json''',
      # See all LED models at https://huggingface.co/models?filter=led
  }
  
  class 					snake_case_							(       lowercase_      ):
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
     __lowerCAmelCase      =						"""led"""
     __lowerCAmelCase      =						{
         """num_attention_heads""": """encoder_attention_heads""",
         """hidden_size""": """d_model""",
         """attention_probs_dropout_prob""": """attention_dropout""",
         """initializer_range""": """init_std""",
     }
  
     def __init__(    self:	int   ,       snake_case__:	str=50_265   ,       snake_case__:	Dict=16_384   ,       snake_case__:	str=1_024   ,       snake_case__:	Tuple=12   ,       snake_case__:	int=4_096   ,       snake_case__:	Union[str, Any]=16   ,       snake_case__:	int=12   ,       snake_case__:	Union[str, Any]=4_096   ,       snake_case__:	Optional[Any]=16   ,       snake_case__:	str=0.0   ,       snake_case__:	Optional[Any]=0.0   ,       snake_case__:	List[Any]=True   ,       snake_case__:	List[Any]=True   ,       snake_case__:	List[Any]="gelu"   ,       snake_case__:	Optional[int]=1_024   ,       snake_case__:	List[Any]=0.1   ,       snake_case__:	int=0.0   ,       snake_case__:	List[str]=0.0   ,       snake_case__:	List[str]=0.02   ,       snake_case__:	Dict=2   ,       snake_case__:	int=0.0   ,       snake_case__:	Optional[int]=1   ,       snake_case__:	Tuple=0   ,       snake_case__:	Union[str, Any]=2   ,       snake_case__:	Union[List[int], int] = 512   ,       **snake_case__:	int   ,       )  ->		List[Any]:
  
  
         """simple docstring"""
  
  
  
         _lowercase     =	vocab_size
         _lowercase     =	max_encoder_position_embeddings
         _lowercase     =	max_decoder_position_embeddings
         _lowercase     =	d_model
         _lowercase     =	encoder_ffn_dim
         _lowercase     =	encoder_layers
         _lowercase     =	encoder_attention_heads
         _lowercase     =	decoder_ffn_dim
         _lowercase     =	decoder_layers
         _lowercase     =	decoder_attention_heads
         _lowercase     =	dropout
         _lowercase     =	attention_dropout
         _lowercase     =	activation_dropout
         _lowercase     =	activation_function
         _lowercase     =	init_std
         _lowercase     =	encoder_layerdrop
         _lowercase     =	decoder_layerdrop
         _lowercase     =	classifier_dropout
         _lowercase     =	use_cache
         _lowercase     =	encoder_layers
         _lowercase     =	attention_window
  
         super().__init__(
             pad_token_id=snake_case__   ,       bos_token_id=snake_case__   ,       eos_token_id=snake_case__   ,       is_encoder_decoder=snake_case__   ,       decoder_start_token_id=snake_case__   ,       **snake_case__   ,       )
  