




import math





class 		A__				:






	def __init__(	self				,     lowerCamelCase				,     lowerCamelCase				,     lowerCamelCase				,     lowerCamelCase						)      ->   Optional[Any]:




						"""simple docstring"""






						__magic_name__					:							Optional[Any]		   =							x
						__magic_name__					:							List[Any]		   =							y
						__magic_name__					:							str		   =							step_size
						__magic_name__					:							List[Any]		   =							function_to_optimize






	def  lowercase      (	self						)      ->   int:




						"""simple docstring"""






						return self.function(self.x				,     self.y						)






	def  lowercase      (	self						)      ->   Dict:




						"""simple docstring"""






						__magic_name__					:							Union[str, Any]		   =							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						)      ->   Optional[int]:




						"""simple docstring"""






						return hash(str(self						)						)






	def __eq__(	self				,     lowerCamelCase						)      ->   Any:




						"""simple docstring"""






						if isinstance(lowerCamelCase__				,     lowerCamelCase__						):
											return hash(str(self						)						) == hash(str(lowerCamelCase__						)						)
						return False






	def __str__(	self						)      ->   int:




						"""simple docstring"""






						return F'''x: {self.x} y: {self.y}'''







def  lowerCAmelCase  (	UpperCAmelCase,	UpperCAmelCase = True,	UpperCAmelCase = math.inf,	UpperCAmelCase = -math.inf,	UpperCAmelCase = math.inf,	UpperCAmelCase = -math.inf,	UpperCAmelCase = False,	UpperCAmelCase = 1_0000,	)  ->int:






					"""simple docstring"""






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

					if visualization:
										from matplotlib import pyplot as plt

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

					return current_state


if __name__ == "__main__":
				import doctest

				doctest.testmod()







				def  lowerCAmelCase  (	UpperCAmelCase,	UpperCAmelCase       )  ->Optional[int]:






									"""simple docstring"""






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

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






									"""simple docstring"""






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

				lowercase_		=							SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
				lowercase_		=							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 copy
from typing import Dict

from ...generation.configuration_utils import GenerationConfig
from ...utils import logging


A							:      Union[str, Any] 	=       logging.get_logger(__name__)






class        SCREAMING_SNAKE_CASE(				__A     ):
       snake_case_ :     List[Any]    =					"""semantic"""

       def __init__(    self					,		lowerCamelCase__=1_0000					,		lowerCamelCase__=True					,		lowerCamelCase__=768					,		lowerCamelCase__=False					,		lowerCamelCase__=False					,		lowerCamelCase__=False					,		lowerCamelCase__=False					,		lowerCamelCase__=0.7					,		lowerCamelCase__=True					,		lowerCamelCase__=1_0048					,		lowerCamelCase__=12_9595					,		lowerCamelCase__=12_9599					,		lowerCamelCase__=1_0000					,		lowerCamelCase__=256					,		lowerCamelCase__=49.9					,		**lowerCamelCase__					,		)    ->					List[Any]:

           """simple docstring"""



           super().__init__(
               temperature=lowerCamelCase__					,		do_sample=lowerCamelCase__					,		eos_token_id=lowerCamelCase__					,		renormalize_logits=lowerCamelCase__					,		max_new_tokens=lowerCamelCase__					,		output_scores=lowerCamelCase__					,		return_dict_in_generate=lowerCamelCase__					,		output_hidden_states=lowerCamelCase__					,		output_attentions=lowerCamelCase__					,		**lowerCamelCase__					,		)

           __lowercase							=						text_encoding_offset
           __lowercase							=						text_pad_token
           __lowercase							=						eos_token_id
           __lowercase							=						semantic_infer_token
           __lowercase							=						semantic_vocab_size
           __lowercase							=						max_input_semantic_length
           __lowercase							=						semantic_rate_hz






class        SCREAMING_SNAKE_CASE(				__A     ):
       snake_case_ :     Optional[int]    =					"""coarse_acoustics"""

       def __init__(    self					,		lowerCamelCase__=True					,		lowerCamelCase__=False					,		lowerCamelCase__=False					,		lowerCamelCase__=False					,		lowerCamelCase__=False					,		lowerCamelCase__=0.7					,		lowerCamelCase__=True					,		lowerCamelCase__=1_2048					,		lowerCamelCase__=75					,		lowerCamelCase__=2					,		lowerCamelCase__=1_2050					,		lowerCamelCase__=256					,		lowerCamelCase__ = 630					,		lowerCamelCase__ = 60					,		**lowerCamelCase__					,		)    ->					Dict:

           """simple docstring"""



           super().__init__(
               temperature=lowerCamelCase__					,		do_sample=lowerCamelCase__					,		renormalize_logits=lowerCamelCase__					,		output_scores=lowerCamelCase__					,		return_dict_in_generate=lowerCamelCase__					,		output_hidden_states=lowerCamelCase__					,		output_attentions=lowerCamelCase__					,		**lowerCamelCase__					,		)

           __lowercase							=						coarse_semantic_pad_token
           __lowercase							=						coarse_rate_hz
           __lowercase							=						n_coarse_codebooks
           __lowercase							=						coarse_infer_token
           __lowercase							=						max_coarse_input_length
           __lowercase							=						max_coarse_history
           __lowercase							=						sliding_window_len






class        SCREAMING_SNAKE_CASE(				__A     ):
       snake_case_ :     Optional[Any]    =					"""fine_acoustics"""

       def __init__(    self					,		lowerCamelCase__=0.5					,		lowerCamelCase__=512					,		lowerCamelCase__=1024					,		lowerCamelCase__=8					,		**lowerCamelCase__					,		)    ->					str:

           """simple docstring"""



           super().__init__(temperature=lowerCamelCase__     )

           __lowercase							=						max_fine_history_length
           __lowercase							=						max_fine_input_length
           __lowercase							=						n_fine_codebooks






class        SCREAMING_SNAKE_CASE(				__A     ):
       snake_case_ :     Optional[Any]    =					"""bark"""
       snake_case_ :     Dict    =					True

       def __init__(    self					,		lowerCamelCase__ = None					,		lowerCamelCase__ = None					,		lowerCamelCase__ = None					,		lowerCamelCase__=2_4000					,		lowerCamelCase__=1024					,		**lowerCamelCase__					,		)    ->					Optional[int]:

           """simple docstring"""



           if semantic_config is None:
               __lowercase							=						{}
               logger.info("""semantic_config is None. initializing the semantic model with default values."""     )

           if coarse_acoustics_config is None:
               __lowercase							=						{}
               logger.info("""coarse_acoustics_config is None. initializing the coarse model with default values."""     )

           if fine_acoustics_config is None:
               __lowercase							=						{}
               logger.info("""fine_acoustics_config is None. initializing the fine model with default values."""     )

           __lowercase							=						BarkSemanticGenerationConfig(**lowerCamelCase__     )
           __lowercase							=						BarkCoarseGenerationConfig(**lowerCamelCase__     )
           __lowercase							=						BarkFineGenerationConfig(**lowerCamelCase__     )

           __lowercase							=						sample_rate
           __lowercase							=						codebook_size

       @classmethod
       def     snake_case__			(    cls					,		lowerCamelCase__					,		lowerCamelCase__					,		lowerCamelCase__					,		**lowerCamelCase__					,		)    ->					Union[str, Any]:

           """simple docstring"""



           return cls(
               semantic_config=semantic_config.to_dict()					,		coarse_acoustics_config=coarse_acoustics_config.to_dict()					,		fine_acoustics_config=fine_acoustics_config.to_dict()					,		**lowerCamelCase__					,		)




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

           """simple docstring"""



           __lowercase							=						copy.deepcopy(self.__dict__     )

           __lowercase							=						self.semantic_config.to_dict()
           __lowercase							=						self.coarse_acoustics_config.to_dict()
           __lowercase							=						self.fine_acoustics_config.to_dict()

           __lowercase							=						self.__class__.model_type
           return output




