





import copy
from typing import Dict

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


__lowerCAmelCase			:Dict	 =     logging.get_logger(__name__)






class 							_a(     __A     ):
		lowerCamelCase__  :Optional[Any] 					=		'semantic'







		def __init__(     self			,    __snake_case=1_0_0_0_0			,    __snake_case=True			,    __snake_case=7_6_8			,    __snake_case=False			,    __snake_case=False			,    __snake_case=False			,    __snake_case=False			,    __snake_case=0.7			,    __snake_case=True			,    __snake_case=1_0_0_4_8			,    __snake_case=1_2_9_5_9_5			,    __snake_case=1_2_9_5_9_9			,    __snake_case=1_0_0_0_0			,    __snake_case=2_5_6			,    __snake_case=49.9			,    **__snake_case			,    )   ->   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			,    )

							_snake_case							:       Union[str, Any]												= text_encoding_offset
							_snake_case							:       str												= text_pad_token
							_snake_case							:       Optional[Any]												= eos_token_id
							_snake_case							:       Dict												= semantic_infer_token
							_snake_case							:       Any												= semantic_vocab_size
							_snake_case							:       str												= max_input_semantic_length
							_snake_case							:       Tuple												= semantic_rate_hz






class 							_a(     __A     ):
		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_2_0_4_8			,    __snake_case=7_5			,    __snake_case=2			,    __snake_case=1_2_0_5_0			,    __snake_case=2_5_6			,    __snake_case = 6_3_0			,    __snake_case = 6_0			,    **__snake_case			,    )   ->   List[Any]:


							'''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			,    )

							_snake_case							:       int												= coarse_semantic_pad_token
							_snake_case							:       Dict												= coarse_rate_hz
							_snake_case							:       Optional[Any]												= n_coarse_codebooks
							_snake_case							:       Dict												= coarse_infer_token
							_snake_case							:       Tuple												= max_coarse_input_length
							_snake_case							:       List[Any]												= max_coarse_history
							_snake_case							:       List[Any]												= sliding_window_len






class 							_a(     __A     ):
		lowerCamelCase__  :Dict 					=		'fine_acoustics'







		def __init__(     self			,    __snake_case=0.5			,    __snake_case=5_1_2			,    __snake_case=1_0_2_4			,    __snake_case=8			,    **__snake_case			,    )   ->   List[Any]:


							'''simple docstring'''

							super().__init__(temperature=__snake_case					)

							_snake_case							:       int												= max_fine_history_length
							_snake_case							:       Optional[Any]												= max_fine_input_length
							_snake_case							:       Any												= n_fine_codebooks






class 							_a(     __A     ):
		lowerCamelCase__  :Tuple 					=		'bark'
		lowerCamelCase__  :List[str] 					=		True







		def __init__(     self			,    __snake_case = None			,    __snake_case = None			,    __snake_case = None			,    __snake_case=2_4_0_0_0			,    __snake_case=1_0_2_4			,    **__snake_case			,    )   ->   Union[str, Any]:


							'''simple docstring'''

							if semantic_config is None:
												_snake_case							:       List[str]												= {}
												logger.info("semantic_config is None. initializing the semantic model with default values."					)

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

							if fine_acoustics_config is None:
												_snake_case							:       Union[str, Any]												= {}
												logger.info("fine_acoustics_config is None. initializing the fine model with default values."					)

							_snake_case							:       List[str]												= BarkSemanticGenerationConfig(**__snake_case					)
							_snake_case							:       Optional[int]												= BarkCoarseGenerationConfig(**__snake_case					)
							_snake_case							:       Tuple												= BarkFineGenerationConfig(**__snake_case					)

							_snake_case							:       Optional[int]												= sample_rate
							_snake_case							:       Any												= codebook_size







		@classmethod
		def 							lowercase							(     cls			,    __snake_case			,    __snake_case			,    __snake_case			,    **__snake_case			,    )   ->   Optional[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()			,    **__snake_case			,    )







		def 							lowercase							(     self					)   ->   Dict:


							'''simple docstring'''

							_snake_case							:       Tuple												= copy.deepcopy(self.__dict__					)

							_snake_case							:       List[str]												= self.semantic_config.to_dict()
							_snake_case							:       int												= self.coarse_acoustics_config.to_dict()
							_snake_case							:       str												= self.fine_acoustics_config.to_dict()

							_snake_case							:       Tuple												= self.__class__.model_type
							return output






def  A					(				UpperCAmelCase					):
					if not isinstance(UpperCAmelCase	,	UpperCAmelCase					):
										_snake_case							:       Optional[Any]												= F"""Input value of [number={number}] must be an integer"""
										raise TypeError(UpperCAmelCase					)
					if number < 1:
										raise ValueError("Input must be a positive integer"					)
					return number * (2 * number - 1)


if __name__ == "__main__":
							import doctest

							doctest.testmod()