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 A_			(lowercase__   ):
  
  
  
  
    '''simple docstring'''
    SCREAMING_SNAKE_CASE__    :		Optional[Any]						  =	"""semantic"""
  
  
  
  
  
  
  
    def __init__(	self       ,     lowercase_=1_0000       ,     lowercase_=True       ,     lowercase_=768       ,     lowercase_=False       ,     lowercase_=False       ,     lowercase_=False       ,     lowercase_=False       ,     lowercase_=0.7       ,     lowercase_=True       ,     lowercase_=1_0048       ,     lowercase_=12_9595       ,     lowercase_=12_9599       ,     lowercase_=1_0000       ,     lowercase_=256       ,     lowercase_=49.9       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       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_      :      Dict      =					text_encoding_offset
       UpperCAmelCase_      :      Dict      =					text_pad_token
       UpperCAmelCase_      :      Optional[int]      =					eos_token_id
       UpperCAmelCase_      :      Optional[Any]      =					semantic_infer_token
       UpperCAmelCase_      :      Tuple      =					semantic_vocab_size
       UpperCAmelCase_      :      Dict      =					max_input_semantic_length
       UpperCAmelCase_      :      List[Any]      =					semantic_rate_hz
  
  
  
  
  class A_			(lowercase__   ):
  
  
  
  
    '''simple docstring'''
    SCREAMING_SNAKE_CASE__    :		Any						  =	"""coarse_acoustics"""
  
  
  
  
  
  
  
    def __init__(	self       ,     lowercase_=True       ,     lowercase_=False       ,     lowercase_=False       ,     lowercase_=False       ,     lowercase_=False       ,     lowercase_=0.7       ,     lowercase_=True       ,     lowercase_=1_2048       ,     lowercase_=75       ,     lowercase_=2       ,     lowercase_=1_2050       ,     lowercase_=256       ,     lowercase_ = 630       ,     lowercase_ = 60       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       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_      :      Optional[int]      =					coarse_semantic_pad_token
       UpperCAmelCase_      :      List[str]      =					coarse_rate_hz
       UpperCAmelCase_      :      List[str]      =					n_coarse_codebooks
       UpperCAmelCase_      :      Optional[Any]      =					coarse_infer_token
       UpperCAmelCase_      :      List[Any]      =					max_coarse_input_length
       UpperCAmelCase_      :      Optional[Any]      =					max_coarse_history
       UpperCAmelCase_      :      Dict      =					sliding_window_len
  
  
  
  
  class A_			(lowercase__   ):
  
  
  
  
    '''simple docstring'''
    SCREAMING_SNAKE_CASE__    :		Dict						  =	"""fine_acoustics"""
  
  
  
  
  
  
  
    def __init__(	self       ,     lowercase_=0.5       ,     lowercase_=512       ,     lowercase_=1024       ,     lowercase_=8       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       super().__init__(temperature=lowercase_						)
  
       UpperCAmelCase_      :      Optional[int]      =					max_fine_history_length
       UpperCAmelCase_      :      Any      =					max_fine_input_length
       UpperCAmelCase_      :      Optional[int]      =					n_fine_codebooks
  
  
  
  
  class A_			(lowercase__   ):
  
  
  
  
    '''simple docstring'''
    SCREAMING_SNAKE_CASE__    :		Tuple						  =	"""bark"""
    SCREAMING_SNAKE_CASE__    :		Any						  =	True
  
  
  
  
  
  
  
    def __init__(	self       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_ = None       ,     lowercase_=2_4000       ,     lowercase_=1024       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       if semantic_config is None:
          UpperCAmelCase_      :      Optional[int]      =					{}
          logger.info("semantic_config is None. initializing the semantic model with default values."						)
  
       if coarse_acoustics_config is None:
          UpperCAmelCase_      :      Tuple      =					{}
          logger.info("coarse_acoustics_config is None. initializing the coarse model with default values."						)
  
       if fine_acoustics_config is None:
          UpperCAmelCase_      :      str      =					{}
          logger.info("fine_acoustics_config is None. initializing the fine model with default values."						)
  
       UpperCAmelCase_      :      List[Any]      =					BarkSemanticGenerationConfig(**lowercase_						)
       UpperCAmelCase_      :      int      =					BarkCoarseGenerationConfig(**lowercase_						)
       UpperCAmelCase_      :      Tuple      =					BarkFineGenerationConfig(**lowercase_						)
  
       UpperCAmelCase_      :      List[str]      =					sample_rate
       UpperCAmelCase_      :      List[str]      =					codebook_size
  
  
  
  
  
  
  
    @classmethod
    def  UpperCamelCase__      (	cls       ,     lowercase_       ,     lowercase_       ,     lowercase_       ,     **lowercase_       ,     ):
  
       """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()       ,     **lowercase_       ,     )
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Any      =					copy.deepcopy(self.__dict__						)
  
       UpperCAmelCase_      :      Dict      =					self.semantic_config.to_dict()
       UpperCAmelCase_      :      Any      =					self.coarse_acoustics_config.to_dict()
       UpperCAmelCase_      :      Union[str, Any]      =					self.fine_acoustics_config.to_dict()
  
       UpperCAmelCase_      :      Dict      =					self.__class__.model_type
       return output
  
  
  
style_context: 
  """simple docstring"""
  
  
  
  
  
  from __future__ import annotations
  
  from statistics import mean
  
  
  
  
  
  
  
  def 			__a  (	__lowerCamelCase						):
     UpperCAmelCase_      :      Dict      =					2
     UpperCAmelCase_      :      Any      =					list(__lowerCamelCase						)
     UpperCAmelCase_      :      List[Any]      =					[0] * len(__lowerCamelCase						)
     UpperCAmelCase_      :      str      =					0
     while True:
        UpperCAmelCase_      :      int      =					True
        for i, burst_time in enumerate(__lowerCamelCase						):
           if rem_burst_times[i] > 0:
              UpperCAmelCase_      :      List[Any]      =					False
              if rem_burst_times[i] > quantum:
                 t += quantum
                 rem_burst_times[i] -= quantum
              else:
                 t += rem_burst_times[i]
                 UpperCAmelCase_      :      Optional[int]      =					t - burst_time
                 UpperCAmelCase_      :      Union[str, Any]      =					0
        if done is True:
           return waiting_times
  
  
  
  
  
  
  
  def 			__a  (	__lowerCamelCase,	__lowerCamelCase						):
     return [burst + waiting for burst, waiting in zip(__lowerCamelCase,	__lowerCamelCase						)]
  
  
  if __name__ == "__main__":
      _a	 =							[3, 5, 7]
      _a	 =							calculate_waiting_times(burst_times)
      _a	 =							calculate_turn_around_times(burst_times, waiting_times)
      print('Process ID \tBurst Time \tWaiting Time \tTurnaround Time')
      for i, burst_time in enumerate(burst_times):
          print(
              f"""  {i + 1}\t\t  {burst_time}\t\t  {waiting_times[i]}\t\t  """
              f"""{turn_around_times[i]}"""
          )
      print(f"""\nAverage waiting time = {mean(waiting_times):.5f}""")
      print(f"""Average turn around time = {mean(turn_around_times):.5f}""")
  
  
  