import copy
from typing import Dict

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


__snake_case			      =    logging.get_logger(__name__)







class 			__snake_case   (     lowerCamelCase__   ):
 __lowerCamelCase    :   int     =      """semantic"""
 def __init__(  self		,   snake_case__=1_0000		,   snake_case__=True		,   snake_case__=768		,   snake_case__=False		,   snake_case__=False		,   snake_case__=False		,   snake_case__=False		,   snake_case__=0.7		,   snake_case__=True		,   snake_case__=1_0048		,   snake_case__=12_9595		,   snake_case__=12_9599		,   snake_case__=1_0000		,   snake_case__=256		,   snake_case__=49.9		,   **snake_case__		,   )	->							List[Any]:
       '''simple docstring'''





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

       UpperCAmelCase    : Tuple      =text_encoding_offset
       UpperCAmelCase    : Tuple      =text_pad_token
       UpperCAmelCase    : Optional[int]      =eos_token_id
       UpperCAmelCase    : int      =semantic_infer_token
       UpperCAmelCase    : List[Any]      =semantic_vocab_size
       UpperCAmelCase    : List[Any]      =max_input_semantic_length
       UpperCAmelCase    : int      =semantic_rate_hz







class 			__snake_case   (     lowerCamelCase__   ):
 __lowerCamelCase    :   Any     =      """coarse_acoustics"""
 def __init__(  self		,   snake_case__=True		,   snake_case__=False		,   snake_case__=False		,   snake_case__=False		,   snake_case__=False		,   snake_case__=0.7		,   snake_case__=True		,   snake_case__=1_2048		,   snake_case__=75		,   snake_case__=2		,   snake_case__=1_2050		,   snake_case__=256		,   snake_case__ = 630		,   snake_case__ = 60		,   **snake_case__		,   )	->							int:
       '''simple docstring'''





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

       UpperCAmelCase    : List[Any]      =coarse_semantic_pad_token
       UpperCAmelCase    : Union[str, Any]      =coarse_rate_hz
       UpperCAmelCase    : Optional[Any]      =n_coarse_codebooks
       UpperCAmelCase    : int      =coarse_infer_token
       UpperCAmelCase    : int      =max_coarse_input_length
       UpperCAmelCase    : int      =max_coarse_history
       UpperCAmelCase    : Dict      =sliding_window_len







class 			__snake_case   (     lowerCamelCase__   ):
 __lowerCamelCase    :   List[str]     =      """fine_acoustics"""
 def __init__(  self		,   snake_case__=0.5		,   snake_case__=512		,   snake_case__=1024		,   snake_case__=8		,   **snake_case__		,   )	->							Tuple:
       '''simple docstring'''





       super().__init__(temperature=snake_case__						)

       UpperCAmelCase    : str      =max_fine_history_length
       UpperCAmelCase    : Any      =max_fine_input_length
       UpperCAmelCase    : str      =n_fine_codebooks







class 			__snake_case   (     lowerCamelCase__   ):
 __lowerCamelCase    :   Dict     =      """bark"""
 __lowerCamelCase    :   List[str]     =      True
 def __init__(  self		,   snake_case__ = None		,   snake_case__ = None		,   snake_case__ = None		,   snake_case__=2_4000		,   snake_case__=1024		,   **snake_case__		,   )	->							List[str]:
       '''simple docstring'''





       if semantic_config is None:
             UpperCAmelCase    : List[Any]      ={}
             logger.info('''semantic_config is None. initializing the semantic model with default values.'''						)

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

       if fine_acoustics_config is None:
             UpperCAmelCase    : List[str]      ={}
             logger.info('''fine_acoustics_config is None. initializing the fine model with default values.'''						)

       UpperCAmelCase    : Union[str, Any]      =BarkSemanticGenerationConfig(**snake_case__						)
       UpperCAmelCase    : Union[str, Any]      =BarkCoarseGenerationConfig(**snake_case__						)
       UpperCAmelCase    : List[Any]      =BarkFineGenerationConfig(**snake_case__						)

       UpperCAmelCase    : int      =sample_rate
       UpperCAmelCase    : int      =codebook_size
 @classmethod
 def 	UpperCAmelCase__       (  cls		,   snake_case__		,   snake_case__		,   snake_case__		,   **snake_case__		,   )	->							List[str]:
       '''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()		,   **snake_case__		,   )






 def 	UpperCAmelCase__       (  self						)	->							List[Any]:
       '''simple docstring'''





       UpperCAmelCase    : str      =copy.deepcopy(self.__dict__						)

       UpperCAmelCase    : int      =self.semantic_config.to_dict()
       UpperCAmelCase    : str      =self.coarse_acoustics_config.to_dict()
       UpperCAmelCase    : Any      =self.fine_acoustics_config.to_dict()

       UpperCAmelCase    : Dict      =self.__class__.model_type
       return output

import math





def   lowerCAmelCase_ (				__lowerCAmelCase						)->  list[int]:






      '''simple docstring'''





      if not isinstance(__lowerCAmelCase		,					__lowerCAmelCase						):
            UpperCAmelCase    : Union[str, Any]      =f'''Input value of [number={number}] must be an integer'''
            raise TypeError(__lowerCAmelCase						)
      if number < 1:
            UpperCAmelCase    : Dict      =f'''Input value of [number={number}] must be a positive integer'''
            raise ValueError(__lowerCAmelCase						)
      UpperCAmelCase    : Dict      =[number]
      while number != 1:
            if number % 2 == 0:
                  UpperCAmelCase    : Optional[Any]      =math.floor(math.sqrt(__lowerCAmelCase						)						)
            else:
                  UpperCAmelCase    : List[str]      =math.floor(
                      math.sqrt(__lowerCAmelCase						) * math.sqrt(__lowerCAmelCase						) * math.sqrt(__lowerCAmelCase						)						)
            sequence.append(__lowerCAmelCase						)
      return sequence


if __name__ == "__main__":
     import doctest

     doctest.testmod()
