

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


lowerCamelCase_					  =   logging.get_logger(__name__)

lowerCamelCase_					  =   {
    '''uclanlp/plbart-base''': '''https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json''',
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}







class 					__lowerCamelCase							(      __lowercase      ):
      lowerCamelCase_      : Optional[Any]  			=   'plbart'
      lowerCamelCase_      : Tuple  			=   ['past_key_values']
      lowerCamelCase_      : List[str]  			=   {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}







      def __init__(	self				,    lowerCamelCase=50005				,    lowerCamelCase=1024				,    lowerCamelCase=6				,    lowerCamelCase=3072				,    lowerCamelCase=12				,    lowerCamelCase=6				,    lowerCamelCase=3072				,    lowerCamelCase=12				,    lowerCamelCase=0.0				,    lowerCamelCase=0.0				,    lowerCamelCase=True				,    lowerCamelCase=True				,    lowerCamelCase="gelu"				,    lowerCamelCase=768				,    lowerCamelCase=0.1				,    lowerCamelCase=0.1				,    lowerCamelCase=0.0				,    lowerCamelCase=0.02				,    lowerCamelCase=0.0				,    lowerCamelCase=True				,    lowerCamelCase=1				,    lowerCamelCase=0				,    lowerCamelCase=2				,    lowerCamelCase=2				,    **lowerCamelCase				,    )		->			str:
        snake_case_					= vocab_size
        snake_case_					= max_position_embeddings
        snake_case_					= d_model
        snake_case_					= encoder_ffn_dim
        snake_case_					= encoder_layers
        snake_case_					= encoder_attention_heads
        snake_case_					= decoder_ffn_dim
        snake_case_					= decoder_layers
        snake_case_					= decoder_attention_heads
        snake_case_					= dropout
        snake_case_					= attention_dropout
        snake_case_					= activation_dropout
        snake_case_					= activation_function
        snake_case_					= init_std
        snake_case_					= encoder_layerdrop
        snake_case_					= decoder_layerdrop
        snake_case_					= classifier_dropout
        snake_case_					= use_cache
        snake_case_					= encoder_layers
        snake_case_					= scale_embedding  # scale factor will be sqrt(d_model) if True
        super().__init__(
            pad_token_id=__A				,    bos_token_id=__A				,    eos_token_id=__A				,    is_encoder_decoder=__A				,    forced_eos_token_id=__A				,    **__A				,    )







class 					__lowerCamelCase							(      __lowercase      ):







      @property
      def       lowerCAmelCase_       (	self  )		->			Mapping[str, Mapping[int, str]]:
        return OrderedDict(
            [
                ("""input_ids""", {0: """batch""", 1: """sequence"""}),
                ("""attention_mask""", {0: """batch""", 1: """sequence"""}),
            ]  )







      @property
      def       lowerCAmelCase_       (	self  )		->			Mapping[str, Mapping[int, str]]:
        if self.use_past:
          return OrderedDict(
              [
                  ("""last_hidden_state""", {0: """batch""", 1: """sequence"""}),
                  ("""past_keys""", {0: """batch""", 2: """sequence"""}),
                  ("""encoder_last_hidden_state""", {0: """batch""", 1: """sequence"""}),
              ]  )
        else:
          return OrderedDict(
              [
                  ("""last_hidden_state""", {0: """batch""", 1: """sequence"""}),
                  ("""encoder_last_hidden_state""", {0: """batch""", 1: """sequence"""}),
              ]  )
'''simple docstring'''

import copy
from typing import Dict

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


lowercase_  		=			logging.get_logger(__name__)
class 	SCREAMING_SNAKE_CASE      (    __lowercase):







		"""simple docstring"""
		lowercase :   Any							=				'semantic'






		def __init__( self		,    __A=1_0000		,    __A=True		,    __A=768		,    __A=False		,    __A=False		,    __A=False		,    __A=False		,    __A=0.7		,    __A=True		,    __A=1_0048		,    __A=12_9595		,    __A=12_9599		,    __A=1_0000		,    __A=256		,    __A=49.9		,    **__A		,    )			->  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		,    )

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

class 	SCREAMING_SNAKE_CASE      (    __lowercase):







		"""simple docstring"""
		lowercase :   Any							=				'coarse_acoustics'






		def __init__( self		,    __A=True		,    __A=False		,    __A=False		,    __A=False		,    __A=False		,    __A=0.7		,    __A=True		,    __A=1_2048		,    __A=75		,    __A=2		,    __A=1_2050		,    __A=256		,    __A = 630		,    __A = 60		,    **__A		,    )			->  Union[str, 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		,    )

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

class 	SCREAMING_SNAKE_CASE      (    __lowercase):







		"""simple docstring"""
		lowercase :   str							=				'fine_acoustics'






		def __init__( self		,    __A=0.5		,    __A=512		,    __A=1024		,    __A=8		,    **__A		,    )			->  int:
								super().__init__(temperature=__A					)

								_lowerCAmelCase					    =max_fine_history_length
								_lowerCAmelCase					    =max_fine_input_length
								_lowerCAmelCase					    =n_fine_codebooks

class 	SCREAMING_SNAKE_CASE      (    __lowercase):







		"""simple docstring"""
		lowercase :   int							=				'bark'
		lowercase :   Optional[Any]							=				True






		def __init__( self		,    __A = None		,    __A = None		,    __A = None		,    __A=2_4000		,    __A=1024		,    **__A		,    )			->  Optional[int]:
								if semantic_config is None:
														_lowerCAmelCase					    ={}
														logger.info('semantic_config is None. initializing the semantic model with default values.'					)

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

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

								_lowerCAmelCase					    =BarkSemanticGenerationConfig(**__A					)
								_lowerCAmelCase					    =BarkCoarseGenerationConfig(**__A					)
								_lowerCAmelCase					    =BarkFineGenerationConfig(**__A					)

								_lowerCAmelCase					    =sample_rate
								_lowerCAmelCase					    =codebook_size






		@classmethod
		def 		UpperCamelCase__							( cls		,    __A		,    __A		,    __A		,    **__A		,    )			->  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()		,    **__A		,    )






		def 		UpperCamelCase__							( self					)			->  Optional[int]:
								_lowerCAmelCase					    =copy.deepcopy(self.__dict__					)

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

								_lowerCAmelCase					    =self.__class__.model_type
								return output





