

import copy
from typing import Dict

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


__A     						=      logging.get_logger(__name__)



class     lowercase_       (    __lowercase	):
      UpperCamelCase_     :						Optional[Any]		 =							"semantic"



      def __init__(     self :							int     ,   A__ :							Optional[Any]=10000     ,   A__ :							int=True     ,   A__ :							int=768     ,   A__ :							List[Any]=False     ,   A__ :							int=False     ,   A__ :							Optional[int]=False     ,   A__ :							int=False     ,   A__ :							str=0.7     ,   A__ :							Any=True     ,   A__ :							Dict=10048     ,   A__ :							Union[str, Any]=129595     ,   A__ :							Any=129599     ,   A__ :							Union[str, Any]=10000     ,   A__ :							Optional[int]=256     ,   A__ :							str=49.9     ,   **A__ :							Union[str, Any]     ,   )       ->	List[Any]:
        super().__init__(
            temperature=A__     ,   do_sample=A__     ,   eos_token_id=A__     ,   renormalize_logits=A__     ,   max_new_tokens=A__     ,   output_scores=A__     ,   return_dict_in_generate=A__     ,   output_hidden_states=A__     ,   output_attentions=A__     ,   **A__     ,   )

        _snake_case		=				text_encoding_offset
        _snake_case		=				text_pad_token
        _snake_case		=				eos_token_id
        _snake_case		=				semantic_infer_token
        _snake_case		=				semantic_vocab_size
        _snake_case		=				max_input_semantic_length
        _snake_case		=				semantic_rate_hz



class     lowercase_       (    __lowercase	):
      UpperCamelCase_     :						Dict		 =							"coarse_acoustics"



      def __init__(     self :							int     ,   A__ :							Union[str, Any]=True     ,   A__ :							Dict=False     ,   A__ :							List[str]=False     ,   A__ :							Tuple=False     ,   A__ :							Tuple=False     ,   A__ :							Tuple=0.7     ,   A__ :							List[str]=True     ,   A__ :							Any=12048     ,   A__ :							List[Any]=75     ,   A__ :							Any=2     ,   A__ :							List[Any]=12050     ,   A__ :							Dict=256     ,   A__ :							int = 630     ,   A__ :							int = 60     ,   **A__ :							Dict     ,   )       ->	Optional[Any]:
        super().__init__(
            temperature=A__     ,   do_sample=A__     ,   renormalize_logits=A__     ,   output_scores=A__     ,   return_dict_in_generate=A__     ,   output_hidden_states=A__     ,   output_attentions=A__     ,   **A__     ,   )

        _snake_case		=				coarse_semantic_pad_token
        _snake_case		=				coarse_rate_hz
        _snake_case		=				n_coarse_codebooks
        _snake_case		=				coarse_infer_token
        _snake_case		=				max_coarse_input_length
        _snake_case		=				max_coarse_history
        _snake_case		=				sliding_window_len



class     lowercase_       (    __lowercase	):
      UpperCamelCase_     :						str		 =							"fine_acoustics"



      def __init__(     self :							Union[str, Any]     ,   A__ :							str=0.5     ,   A__ :							List[str]=512     ,   A__ :							List[str]=1024     ,   A__ :							List[str]=8     ,   **A__ :							List[str]     ,   )       ->	Tuple:
        super().__init__(temperature=A__						)

        _snake_case		=				max_fine_history_length
        _snake_case		=				max_fine_input_length
        _snake_case		=				n_fine_codebooks



class     lowercase_       (    __lowercase	):
      UpperCamelCase_     :						Union[str, Any]		 =							"bark"
      UpperCamelCase_     :						List[Any]		 =							True



      def __init__(     self :							Any     ,   A__ :							Dict = None     ,   A__ :							Dict = None     ,   A__ :							Dict = None     ,   A__ :							str=24000     ,   A__ :							int=1024     ,   **A__ :							Any     ,   )       ->	int:
        if semantic_config is None:
          _snake_case		=				{}
          logger.info('''semantic_config is None. initializing the semantic model with default values.'''						)

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

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

        _snake_case		=				BarkSemanticGenerationConfig(**A__						)
        _snake_case		=				BarkCoarseGenerationConfig(**A__						)
        _snake_case		=				BarkFineGenerationConfig(**A__						)

        _snake_case		=				sample_rate
        _snake_case		=				codebook_size



      @classmethod
      def 		UpperCamelCase_						(     cls :							List[Any]     ,   A__ :							BarkSemanticGenerationConfig     ,   A__ :							BarkCoarseGenerationConfig     ,   A__ :							BarkFineGenerationConfig     ,   **A__ :							str     ,   )       ->	str:
        return cls(
            semantic_config=semantic_config.to_dict()     ,   coarse_acoustics_config=coarse_acoustics_config.to_dict()     ,   fine_acoustics_config=fine_acoustics_config.to_dict()     ,   **A__     ,   )







      def 		UpperCamelCase_						(     self :							int						)       ->	Dict:
        _snake_case		=				copy.deepcopy(self.__dict__						)

        _snake_case		=				self.semantic_config.to_dict()
        _snake_case		=				self.coarse_acoustics_config.to_dict()
        _snake_case		=				self.fine_acoustics_config.to_dict()

        _snake_case		=				self.__class__.model_type
        return output




import warnings

from ...utils import logging
from .image_processing_detr import DetrImageProcessor


__A     						=      logging.get_logger(__name__)



class     lowercase_       (    __lowercase	):



      def __init__(     self :							List[str]     ,   *A__ :							Tuple     ,   **A__ :							int						)       ->	None:
        warnings.warn(
            '''The class DetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
            ''' Please use DetrImageProcessor instead.'''     ,   A__     ,   )
        super().__init__(*A__     ,   **A__						)

