code: 
  
  
  
  
  
  
  """simple docstring"""
  
  
  
  
  
  
  import copy
  from typing import Dict
  
  from ...generation.configuration_utils import GenerationConfig
  from ...utils import logging
  
  
  A_			  =    logging.get_logger(__name__)
  class 						__lowerCAmelCase   (			lowerCamelCase__       ):
  
  
  
  
  
  
  
  		'''simple docstring'''
  
  
  		__lowerCamelCase       :    Optional[Any]     	=			'semantic'
  		def __init__(      self:		Optional[int]				,			UpperCamelCase_:		Dict=1_0000				,			UpperCamelCase_:		Optional[Any]=True				,			UpperCamelCase_:		int=768				,			UpperCamelCase_:		Dict=False				,			UpperCamelCase_:		Union[str, Any]=False				,			UpperCamelCase_:		str=False				,			UpperCamelCase_:		Dict=False				,			UpperCamelCase_:		str=0.7				,			UpperCamelCase_:		int=True				,			UpperCamelCase_:		List[str]=1_0048				,			UpperCamelCase_:		Union[str, Any]=12_9595				,			UpperCamelCase_:		Optional[Any]=12_9599				,			UpperCamelCase_:		Union[str, Any]=1_0000				,			UpperCamelCase_:		List[str]=256				,			UpperCamelCase_:		int=49.9				,			**UpperCamelCase_:		List[Any]				,			):
  					super().__init__(
  					    temperature=lowercase_				,			do_sample=lowercase_				,			eos_token_id=lowercase_				,			renormalize_logits=lowercase_				,			max_new_tokens=lowercase_				,			output_scores=lowercase_				,			return_dict_in_generate=lowercase_				,			output_hidden_states=lowercase_				,			output_attentions=lowercase_				,			**lowercase_				,			)
  
  					UpperCamelCase_     =text_encoding_offset
  					UpperCamelCase_     =text_pad_token
  					UpperCamelCase_     =eos_token_id
  					UpperCamelCase_     =semantic_infer_token
  					UpperCamelCase_     =semantic_vocab_size
  					UpperCamelCase_     =max_input_semantic_length
  					UpperCamelCase_     =semantic_rate_hz
  
  
  
  
  class 						__lowerCAmelCase   (			lowerCamelCase__       ):
  
  
  
  
  
  
  
  		'''simple docstring'''
  
  
  		__lowerCamelCase       :    int     	=			'coarse_acoustics'
  		def __init__(      self:		Any				,			UpperCamelCase_:		List[str]=True				,			UpperCamelCase_:		Dict=False				,			UpperCamelCase_:		Optional[Any]=False				,			UpperCamelCase_:		Union[str, Any]=False				,			UpperCamelCase_:		Dict=False				,			UpperCamelCase_:		Any=0.7				,			UpperCamelCase_:		Union[str, Any]=True				,			UpperCamelCase_:		List[str]=1_2048				,			UpperCamelCase_:		List[Any]=75				,			UpperCamelCase_:		Union[str, Any]=2				,			UpperCamelCase_:		Any=1_2050				,			UpperCamelCase_:		Union[str, Any]=256				,			UpperCamelCase_:		Tuple = 630				,			UpperCamelCase_:		Optional[Any] = 60				,			**UpperCamelCase_:		Any				,			):
  					super().__init__(
  					    temperature=lowercase_				,			do_sample=lowercase_				,			renormalize_logits=lowercase_				,			output_scores=lowercase_				,			return_dict_in_generate=lowercase_				,			output_hidden_states=lowercase_				,			output_attentions=lowercase_				,			**lowercase_				,			)
  
  					UpperCamelCase_     =coarse_semantic_pad_token
  					UpperCamelCase_     =coarse_rate_hz
  					UpperCamelCase_     =n_coarse_codebooks
  					UpperCamelCase_     =coarse_infer_token
  					UpperCamelCase_     =max_coarse_input_length
  					UpperCamelCase_     =max_coarse_history
  					UpperCamelCase_     =sliding_window_len
  
  
  
  
  class 						__lowerCAmelCase   (			lowerCamelCase__       ):
  
  
  
  
  
  
  
  		'''simple docstring'''
  
  
  		__lowerCamelCase       :    List[str]     	=			'fine_acoustics'
  		def __init__(      self:		List[Any]				,			UpperCamelCase_:		Dict=0.5				,			UpperCamelCase_:		int=512				,			UpperCamelCase_:		str=1024				,			UpperCamelCase_:		int=8				,			**UpperCamelCase_:		Dict				,			):
  					super().__init__(temperature=lowercase_					)
  
  					UpperCamelCase_     =max_fine_history_length
  					UpperCamelCase_     =max_fine_input_length
  					UpperCamelCase_     =n_fine_codebooks
  
  
  
  
  class 						__lowerCAmelCase   (			lowerCamelCase__       ):
  
  
  
  
  
  
  
  		'''simple docstring'''
  
  
  		__lowerCamelCase       :    Dict     	=			'bark'
  		__lowerCamelCase       :    Optional[int]     	=			True
  		def __init__(      self:		str				,			UpperCamelCase_:		List[str] = None				,			UpperCamelCase_:		List[Any] = None				,			UpperCamelCase_:		List[str] = None				,			UpperCamelCase_:		Tuple=2_4000				,			UpperCamelCase_:		Optional[int]=1024				,			**UpperCamelCase_:		str				,			):
  
  
  
  
  
  
  					if semantic_config is None:
  								UpperCamelCase_     ={}
  								logger.info("semantic_config is None. initializing the semantic model with default values."					)
  
  					if coarse_acoustics_config is None:
  								UpperCamelCase_     ={}
  								logger.info("coarse_acoustics_config is None. initializing the coarse model with default values."					)
  
  					if fine_acoustics_config is None:
  								UpperCamelCase_     ={}
  								logger.info("fine_acoustics_config is None. initializing the fine model with default values."					)
  
  					UpperCamelCase_     =BarkSemanticGenerationConfig(**lowercase_					)
  					UpperCamelCase_     =BarkCoarseGenerationConfig(**lowercase_					)
  					UpperCamelCase_     =BarkFineGenerationConfig(**lowercase_					)
  
  					UpperCamelCase_     =sample_rate
  					UpperCamelCase_     =codebook_size
  		@classmethod
  		def 					UpperCamelCase__   (      cls:		Tuple				,			UpperCamelCase_:		List[str]				,			UpperCamelCase_:		str				,			UpperCamelCase_:		Optional[int]				,			**UpperCamelCase_:		Dict				,			):
  					return cls(
  					    semantic_config=semantic_config.to_dict()				,			coarse_acoustics_config=coarse_acoustics_config.to_dict()				,			fine_acoustics_config=fine_acoustics_config.to_dict()				,			**lowercase_				,			)
  
  
  
  
  
  		def 					UpperCamelCase__   (      self:		int					):
  					UpperCamelCase_     =copy.deepcopy(self.__dict__					)
  
  					UpperCamelCase_     =self.semantic_config.to_dict()
  					UpperCamelCase_     =self.coarse_acoustics_config.to_dict()
  					UpperCamelCase_     =self.fine_acoustics_config.to_dict()
  
  					UpperCamelCase_     =self.__class__.model_type
  					return output
  
style_context: 
  
  
  
  
  
  
  """simple docstring"""
  
  
  
  
  
  
  from .hash_table import HashTable
  from .number_theory.prime_numbers import is_prime, next_prime
  class 						__lowerCAmelCase   (			UpperCAmelCase       ):
  
  
  
  
  
  
  
    '''simple docstring'''
  
  
    def __init__(      self:		List[Any]				,			*UpperCamelCase_:		Dict				,			**UpperCamelCase_:		Optional[int]					):
       super().__init__(*UpperCamelCase_				,			**UpperCamelCase_					)
    def 					UpperCamelCase__   (      self:		Any				,			UpperCamelCase_:		Optional[int]				,			UpperCamelCase_:		Optional[int]					):
       UpperCamelCase_     =(
           next_prime(value % self.size_table					)
           if not is_prime(value % self.size_table					)
           else value % self.size_table
       )  # gt = bigger than
       return next_prime_gt - (data % next_prime_gt)
    def 					UpperCamelCase__   (      self:		str				,			UpperCamelCase_:		List[str]				,			UpperCamelCase_:		str				,			UpperCamelCase_:		Tuple					):
       return (increment * self.__hash_function_a(UpperCamelCase_				,			UpperCamelCase_					)) % self.size_table
  
  
  
  
  
    def 					UpperCamelCase__   (      self:		str				,			UpperCamelCase_:		int				,			UpperCamelCase_:		str=None					):
       UpperCamelCase_     =1
       UpperCamelCase_     =self.hash_function(UpperCamelCase_					)
  
       while self.values[new_key] is not None and self.values[new_key] != key:
          UpperCamelCase_     =(
              self.__hash_double_function(UpperCamelCase_				,			UpperCamelCase_				,			UpperCamelCase_					)
              if self.balanced_factor() >= self.lim_charge
              else None
          )
          if new_key is None:
             break
          else:
             i += 1
  
       return new_key
  