"""simple docstring"""







import numpy as np  # noqa: E402

from ...configuration_utils import ConfigMixin, register_to_config
from ...schedulers.scheduling_utils import SchedulerMixin


try:
     import librosa  # noqa: E402

     _SCREAMING_SNAKE_CASE	:		Tuple   =   True
     _SCREAMING_SNAKE_CASE	:		int   =   ''''''
except Exception as e:
     _SCREAMING_SNAKE_CASE	:		Optional[int]   =   False
     _SCREAMING_SNAKE_CASE	:		Any   =   (
         F"Cannot import librosa because {e}. Make sure to correctly install librosa to be able to install it."
     )


from PIL import Image  # noqa: E402






class      _SCREAMING_SNAKE_CASE							(			UpperCAmelCase    ,				UpperCAmelCase				):



   '''simple docstring'''



   __UpperCAmelCase	:							int    =    "mel_config.json"







   @register_to_config
   def __init__(	self ,				_SCREAMING_SNAKE_CASE = 256 ,				_SCREAMING_SNAKE_CASE = 256 ,				_SCREAMING_SNAKE_CASE = 22050 ,				_SCREAMING_SNAKE_CASE = 2048 ,				_SCREAMING_SNAKE_CASE = 512 ,				_SCREAMING_SNAKE_CASE = 80 ,				_SCREAMING_SNAKE_CASE = 32 ,				):


      '''simple docstring'''

      __lowerCamelCase    		=					hop_length
      __lowerCamelCase    		=					sample_rate
      __lowerCamelCase    		=					n_fft
      __lowerCamelCase    		=					top_db
      __lowerCamelCase    		=					n_iter
      self.set_resolution(_SCREAMING_SNAKE_CASE ,				_SCREAMING_SNAKE_CASE	)
      __lowerCamelCase    		=					None

      if not _librosa_can_be_imported:
         raise ValueError(_import_error	)







   def    _A				(	self ,				_SCREAMING_SNAKE_CASE ,				_SCREAMING_SNAKE_CASE	):


      '''simple docstring'''

      __lowerCamelCase    		=					x_res
      __lowerCamelCase    		=					y_res
      __lowerCamelCase    		=					self.y_res
      __lowerCamelCase    		=					self.x_res * self.hop_length - 1







   def    _A				(	self ,				_SCREAMING_SNAKE_CASE = None ,				_SCREAMING_SNAKE_CASE = None	):


      '''simple docstring'''

      if audio_file is not None:
         __lowerCamelCase    		=					librosa.load(_SCREAMING_SNAKE_CASE ,				mono=_SCREAMING_SNAKE_CASE ,				sr=self.sr	)
      else:
         __lowerCamelCase    		=					raw_audio

      # Pad with silence if necessary.
      if len(self.audio	) < self.x_res * self.hop_length:
         __lowerCamelCase    		=					np.concatenate([self.audio, np.zeros((self.x_res * self.hop_length - len(self.audio	),)	)]	)







   def    _A				(	self	):


      '''simple docstring'''

      return len(self.audio	) // self.slice_size







   def    _A				(	self ,				_SCREAMING_SNAKE_CASE = 0	):


      '''simple docstring'''

      return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]







   def    _A				(	self	):


      '''simple docstring'''

      return self.sr







   def    _A				(	self ,				_SCREAMING_SNAKE_CASE	):


      '''simple docstring'''

      __lowerCamelCase    		=					librosa.feature.melspectrogram(
          y=self.get_audio_slice(_SCREAMING_SNAKE_CASE	) ,				sr=self.sr ,				n_fft=self.n_fft ,				hop_length=self.hop_length ,				n_mels=self.n_mels	)
      __lowerCamelCase    		=					librosa.power_to_db(_SCREAMING_SNAKE_CASE ,				ref=np.max ,				top_db=self.top_db	)
      __lowerCamelCase    		=					(((log_S + self.top_db) * 255 / self.top_db).clip(0 ,				255	) + 0.5).astype(np.uinta	)
      __lowerCamelCase    		=					Image.fromarray(_SCREAMING_SNAKE_CASE	)
      return image







   def    _A				(	self ,				_SCREAMING_SNAKE_CASE	):


      '''simple docstring'''

      __lowerCamelCase    		=					np.frombuffer(image.tobytes() ,				dtype='uint8'	).reshape((image.height, image.width)	)
      __lowerCamelCase    		=					bytedata.astype('float'	) * self.top_db / 255 - self.top_db
      __lowerCamelCase    		=					librosa.db_to_power(_SCREAMING_SNAKE_CASE	)
      __lowerCamelCase    		=					librosa.feature.inverse.mel_to_audio(
          _SCREAMING_SNAKE_CASE ,				sr=self.sr ,				n_fft=self.n_fft ,				hop_length=self.hop_length ,				n_iter=self.n_iter	)
      return audio














import copy
from typing import Dict

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


__lowerCamelCase						= logging.get_logger(__name__)

class      UpperCamelCase_							(				UpperCamelCase       ):
						lowercase									=  '''semantic'''




						def __init__(    self		,	lowercase=10_000		,	lowercase=True		,	lowercase=768		,	lowercase=False		,	lowercase=False		,	lowercase=False		,	lowercase=False		,	lowercase=0.7		,	lowercase=True		,	lowercase=10_048		,	lowercase=129_595		,	lowercase=129_599		,	lowercase=10_000		,	lowercase=256		,	lowercase=49.9		,	**lowercase		,	)			->						int:
													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		,	)

													_a  :    Optional[int]			=						text_encoding_offset
													_a  :    str			=						text_pad_token
													_a  :    List[str]			=						eos_token_id
													_a  :    Tuple			=						semantic_infer_token
													_a  :    int			=						semantic_vocab_size
													_a  :    List[str]			=						max_input_semantic_length
													_a  :    Union[str, Any]			=						semantic_rate_hz

class      UpperCamelCase_							(				UpperCamelCase       ):
						lowercase									=  '''coarse_acoustics'''




						def __init__(    self		,	lowercase=True		,	lowercase=False		,	lowercase=False		,	lowercase=False		,	lowercase=False		,	lowercase=0.7		,	lowercase=True		,	lowercase=12_048		,	lowercase=75		,	lowercase=2		,	lowercase=12_050		,	lowercase=256		,	lowercase = 630		,	lowercase = 60		,	**lowercase		,	)			->						List[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		,	)

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

class      UpperCamelCase_							(				UpperCamelCase       ):
						lowercase									=  '''fine_acoustics'''




						def __init__(    self		,	lowercase=0.5		,	lowercase=512		,	lowercase=1_024		,	lowercase=8		,	**lowercase		,	)			->						str:
													super().__init__(temperature=lowercase       )

													_a  :    Tuple			=						max_fine_history_length
													_a  :    Tuple			=						max_fine_input_length
													_a  :    Any			=						n_fine_codebooks

class      UpperCamelCase_							(				UpperCamelCase       ):
						lowercase									=  '''bark'''
						lowercase									=  True




						def __init__(    self		,	lowercase = None		,	lowercase = None		,	lowercase = None		,	lowercase=24_000		,	lowercase=1_024		,	**lowercase		,	)			->						List[str]:
													if semantic_config is None:
																				_a  :    str			=						{}
																				logger.info('''semantic_config is None. initializing the semantic model with default values.'''       )

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

													if fine_acoustics_config is None:
																				_a  :    int			=						{}
																				logger.info('''fine_acoustics_config is None. initializing the fine model with default values.'''       )

													_a  :    List[Any]			=						BarkSemanticGenerationConfig(**lowercase       )
													_a  :    Union[str, Any]			=						BarkCoarseGenerationConfig(**lowercase       )
													_a  :    str			=						BarkFineGenerationConfig(**lowercase       )

													_a  :    List[str]			=						sample_rate
													_a  :    str			=						codebook_size




						@classmethod
						def      snake_case__(    cls		,	lowercase		,	lowercase		,	lowercase		,	**lowercase		,	)			->						List[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()		,	**lowercase		,	)







						def      snake_case__(    self       )			->						List[str]:
													_a  :    Any			=						copy.deepcopy(self.__dict__       )

													_a  :    str			=						self.semantic_config.to_dict()
													_a  :    Any			=						self.coarse_acoustics_config.to_dict()
													_a  :    Union[str, Any]			=						self.fine_acoustics_config.to_dict()

													_a  :    List[str]			=						self.__class__.model_type
													return output