code: 
  
  
  
  
  
  
  import copy
  from typing import Dict
  
  from ...generation.configuration_utils import GenerationConfig
  from ...utils import logging
  
  
  __A  							=  logging.get_logger(__name__)
  
  
  
  class 							_A (    UpperCamelCase							):
      """simple docstring"""
  
      lowerCamelCase  :       Optional[int]   =   'semantic'
  
  
  
      def __init__(							self			:    Optional[int]   ,    __SCREAMING_SNAKE_CASE			:    Optional[int]=10000   ,    __SCREAMING_SNAKE_CASE			:    str=True   ,    __SCREAMING_SNAKE_CASE			:    Optional[Any]=768   ,    __SCREAMING_SNAKE_CASE			:    Optional[int]=False   ,    __SCREAMING_SNAKE_CASE			:    Optional[int]=False   ,    __SCREAMING_SNAKE_CASE			:    Optional[Any]=False   ,    __SCREAMING_SNAKE_CASE			:    int=False   ,    __SCREAMING_SNAKE_CASE			:    Dict=0.7   ,    __SCREAMING_SNAKE_CASE			:    List[Any]=True   ,    __SCREAMING_SNAKE_CASE			:    List[str]=10048   ,    __SCREAMING_SNAKE_CASE			:    Optional[int]=129595   ,    __SCREAMING_SNAKE_CASE			:    Tuple=129599   ,    __SCREAMING_SNAKE_CASE			:    Tuple=10000   ,    __SCREAMING_SNAKE_CASE			:    Any=256   ,    __SCREAMING_SNAKE_CASE			:    str=49.9   ,    **__SCREAMING_SNAKE_CASE			:    int   ,    )			->       int:
             super().__init__(
                 temperature=__SCREAMING_SNAKE_CASE   ,    do_sample=__SCREAMING_SNAKE_CASE   ,    eos_token_id=__SCREAMING_SNAKE_CASE   ,    renormalize_logits=__SCREAMING_SNAKE_CASE   ,    max_new_tokens=__SCREAMING_SNAKE_CASE   ,    output_scores=__SCREAMING_SNAKE_CASE   ,    return_dict_in_generate=__SCREAMING_SNAKE_CASE   ,    output_hidden_states=__SCREAMING_SNAKE_CASE   ,    output_attentions=__SCREAMING_SNAKE_CASE   ,    **__SCREAMING_SNAKE_CASE   ,    )
  
             __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 							_A (    UpperCamelCase							):
      """simple docstring"""
  
      lowerCamelCase  :       str   =   'coarse_acoustics'
  
  
  
      def __init__(							self			:    Tuple   ,    __SCREAMING_SNAKE_CASE			:    List[str]=True   ,    __SCREAMING_SNAKE_CASE			:    Tuple=False   ,    __SCREAMING_SNAKE_CASE			:    List[Any]=False   ,    __SCREAMING_SNAKE_CASE			:    List[Any]=False   ,    __SCREAMING_SNAKE_CASE			:    Optional[Any]=False   ,    __SCREAMING_SNAKE_CASE			:    Optional[int]=0.7   ,    __SCREAMING_SNAKE_CASE			:    Optional[int]=True   ,    __SCREAMING_SNAKE_CASE			:    Optional[int]=12048   ,    __SCREAMING_SNAKE_CASE			:    Optional[Any]=75   ,    __SCREAMING_SNAKE_CASE			:    Union[str, Any]=2   ,    __SCREAMING_SNAKE_CASE			:    Dict=12050   ,    __SCREAMING_SNAKE_CASE			:    Optional[Any]=256   ,    __SCREAMING_SNAKE_CASE			:    int = 630   ,    __SCREAMING_SNAKE_CASE			:    int = 60   ,    **__SCREAMING_SNAKE_CASE			:    Optional[int]   ,    )			->       Union[str, Any]:
             super().__init__(
                 temperature=__SCREAMING_SNAKE_CASE   ,    do_sample=__SCREAMING_SNAKE_CASE   ,    renormalize_logits=__SCREAMING_SNAKE_CASE   ,    output_scores=__SCREAMING_SNAKE_CASE   ,    return_dict_in_generate=__SCREAMING_SNAKE_CASE   ,    output_hidden_states=__SCREAMING_SNAKE_CASE   ,    output_attentions=__SCREAMING_SNAKE_CASE   ,    **__SCREAMING_SNAKE_CASE   ,    )
  
             __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 							_A (    UpperCamelCase							):
      """simple docstring"""
  
      lowerCamelCase  :       Any   =   'fine_acoustics'
  
  
  
      def __init__(							self			:    List[str]   ,    __SCREAMING_SNAKE_CASE			:    List[Any]=0.5   ,    __SCREAMING_SNAKE_CASE			:    List[str]=512   ,    __SCREAMING_SNAKE_CASE			:    Any=1024   ,    __SCREAMING_SNAKE_CASE			:    Optional[Any]=8   ,    **__SCREAMING_SNAKE_CASE			:    int   ,    )			->       Dict:
             super().__init__(temperature=__SCREAMING_SNAKE_CASE			)
  
             __UpperCAmelCase    							=max_fine_history_length
             __UpperCAmelCase    							=max_fine_input_length
             __UpperCAmelCase    							=n_fine_codebooks
  
  
  
  
  class 							_A (    UpperCamelCase							):
      """simple docstring"""
  
      lowerCamelCase  :       Union[str, Any]   =   'bark'
      lowerCamelCase  :       Optional[int]   =   True
  
  
  
      def __init__(							self			:    Dict   ,    __SCREAMING_SNAKE_CASE			:    Dict = None   ,    __SCREAMING_SNAKE_CASE			:    Dict = None   ,    __SCREAMING_SNAKE_CASE			:    Dict = None   ,    __SCREAMING_SNAKE_CASE			:    List[Any]=24000   ,    __SCREAMING_SNAKE_CASE			:    Dict=1024   ,    **__SCREAMING_SNAKE_CASE			:    Tuple   ,    )			->       Union[str, Any]:
             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(**__SCREAMING_SNAKE_CASE			)
             __UpperCAmelCase    							=BarkCoarseGenerationConfig(**__SCREAMING_SNAKE_CASE			)
             __UpperCAmelCase    							=BarkFineGenerationConfig(**__SCREAMING_SNAKE_CASE			)
  
             __UpperCAmelCase    							=sample_rate
             __UpperCAmelCase    							=codebook_size
  
  
  
      @classmethod
      def _a       (							cls			:    Optional[int]   ,    __SCREAMING_SNAKE_CASE			:    BarkSemanticGenerationConfig   ,    __SCREAMING_SNAKE_CASE			:    BarkCoarseGenerationConfig   ,    __SCREAMING_SNAKE_CASE			:    BarkFineGenerationConfig   ,    **__SCREAMING_SNAKE_CASE			:    int   ,    )			->       Union[str, Any]:
             return cls(
                 semantic_config=semantic_config.to_dict()   ,    coarse_acoustics_config=coarse_acoustics_config.to_dict()   ,    fine_acoustics_config=fine_acoustics_config.to_dict()   ,    **__SCREAMING_SNAKE_CASE   ,    )
  
  
  
      def _a       (							self			:    Any			)			->       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: 
  
  
  
  
  
  
  from __future__ import annotations
  
  __A  							=  [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]
  
  
  
  class 							_A :
      """simple docstring"""
  
      def __init__(							self			:    List[str]   ,    __SCREAMING_SNAKE_CASE			:    int			)			->       None:
             __UpperCAmelCase    							=-1
             __UpperCAmelCase    							=-1
             __UpperCAmelCase    							=[-1] * length
             __UpperCAmelCase    							=None
             __UpperCAmelCase    							=None
  
  
  
      def __repr__(							self			:    Optional[int]			)			->       str:
             return f'''Node(min_value={self.minn} max_value={self.maxx})'''
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	list[int]		)  ->							Node | None:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=Node(len(A_		)		)
         __UpperCAmelCase							,   __UpperCAmelCase    							=min(A_		), max(A_		)
         # Leaf node case where the node contains only one unique value
         if root.minn == root.maxx:
                return root
         __UpperCAmelCase    							=(root.minn + root.maxx) // 2
  
         __UpperCAmelCase    							=[]
         __UpperCAmelCase    							=[]
  
         for index, num in enumerate(A_		):
                if num <= pivot:
                       left_arr.append(A_		)
                else:
                       right_arr.append(A_		)
                __UpperCAmelCase    							=len(A_		)
         __UpperCAmelCase    							=build_tree(A_		)
         __UpperCAmelCase    							=build_tree(A_		)
         return root
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int		)  ->							int:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if index < 0 or node is None:
                return 0
         # Leaf node cases
         if node.minn == node.maxx:
                return index + 1 if node.minn == num else 0
         __UpperCAmelCase    							=(node.minn + node.maxx) // 2
         if num <= pivot:
                # go the left subtree and map index to the left subtree
                return rank_till_index(node.left     ,			A_     ,			node.map_left[index] - 1		)
         else:
                # go to the right subtree and map index to the right subtree
                return rank_till_index(node.right     ,			A_     ,			index - node.map_left[index]		)
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int     ,			A_:	int		)  ->							int:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if start > end:
                return 0
         __UpperCAmelCase    							=rank_till_index(A_     ,			A_     ,			A_		)
         __UpperCAmelCase    							=rank_till_index(A_     ,			A_     ,			start - 1		)
         return rank_till_end - rank_before_start
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int     ,			A_:	int		)  ->							int:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if index > (end - start) or start > end or node is None:
                return -1
         # Leaf node case
         if node.minn == node.maxx:
                return node.minn
         # Number of elements in the left subtree in interval [start, end]
         __UpperCAmelCase    							=node.map_left[end] - (
             node.map_left[start - 1] if start else 0
         )
         if num_elements_in_left_tree > index:
                return quantile(
                    node.left     ,			A_     ,			(node.map_left[start - 1] if start else 0)     ,			node.map_left[end] - 1     ,			)
         else:
                return quantile(
                    node.right     ,			index - num_elements_in_left_tree     ,			start - (node.map_left[start - 1] if start else 0)     ,			end - node.map_left[end]     ,			)
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int     ,			A_:	int     ,			A_:	int		)  ->							int:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if (
             start > end
             or node is None
             or start_num > end_num
             or node.minn > end_num
             or node.maxx < start_num
         ):
                return 0
         if start_num <= node.minn and node.maxx <= end_num:
                return end - start + 1
         __UpperCAmelCase    							=range_counting(
             node.left     ,			(node.map_left[start - 1] if start else 0)     ,			node.map_left[end] - 1     ,			A_     ,			A_     ,			)
         __UpperCAmelCase    							=range_counting(
             node.right     ,			start - (node.map_left[start - 1] if start else 0)     ,			end - node.map_left[end]     ,			A_     ,			A_     ,			)
         return left + right
  
  
  if __name__ == "__main__":
     import doctest
  
     doctest.testmod()
  
  
  
  
  