code: import copy
  from typing import Dict
  
  from ...generation.configuration_utils import GenerationConfig
  from ...utils import logging
  
  
  lowerCamelCase__           =				logging.get_logger(__name__)
  
  
  
  
  class 					UpperCamelCase	(     snake_case__      ):
  					__UpperCamelCase						=   """semantic"""
  
  
  
  
  					def __init__( self :					int      ,_lowerCAmelCase :					int=10_000      ,_lowerCAmelCase :					Optional[int]=True      ,_lowerCAmelCase :					List[Any]=768      ,_lowerCAmelCase :					int=False      ,_lowerCAmelCase :					Any=False      ,_lowerCAmelCase :					List[Any]=False      ,_lowerCAmelCase :					List[Any]=False      ,_lowerCAmelCase :					Tuple=0.7      ,_lowerCAmelCase :					Optional[Any]=True      ,_lowerCAmelCase :					Union[str, Any]=10_048      ,_lowerCAmelCase :					List[str]=129_595      ,_lowerCAmelCase :					Any=129_599      ,_lowerCAmelCase :					List[Any]=10_000      ,_lowerCAmelCase :					Optional[int]=256      ,_lowerCAmelCase :					Tuple=4_9.9      ,**_lowerCAmelCase :					Optional[Any]      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(
  							    temperature=_lowerCAmelCase      ,do_sample=_lowerCAmelCase      ,eos_token_id=_lowerCAmelCase      ,renormalize_logits=_lowerCAmelCase      ,max_new_tokens=_lowerCAmelCase      ,output_scores=_lowerCAmelCase      ,return_dict_in_generate=_lowerCAmelCase      ,output_hidden_states=_lowerCAmelCase      ,output_attentions=_lowerCAmelCase      ,**_lowerCAmelCase      ,)
  
  							__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 					UpperCamelCase	(     snake_case__      ):
  					__UpperCamelCase						=   """coarse_acoustics"""
  
  
  
  
  					def __init__( self :					str      ,_lowerCAmelCase :					Optional[Any]=True      ,_lowerCAmelCase :					str=False      ,_lowerCAmelCase :					Optional[Any]=False      ,_lowerCAmelCase :					List[Any]=False      ,_lowerCAmelCase :					Union[str, Any]=False      ,_lowerCAmelCase :					str=0.7      ,_lowerCAmelCase :					str=True      ,_lowerCAmelCase :					Optional[int]=12_048      ,_lowerCAmelCase :					Tuple=75      ,_lowerCAmelCase :					Optional[int]=2      ,_lowerCAmelCase :					Union[str, Any]=12_050      ,_lowerCAmelCase :					Dict=256      ,_lowerCAmelCase :					int = 630      ,_lowerCAmelCase :					int = 60      ,**_lowerCAmelCase :					Dict      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(
  							    temperature=_lowerCAmelCase      ,do_sample=_lowerCAmelCase      ,renormalize_logits=_lowerCAmelCase      ,output_scores=_lowerCAmelCase      ,return_dict_in_generate=_lowerCAmelCase      ,output_hidden_states=_lowerCAmelCase      ,output_attentions=_lowerCAmelCase      ,**_lowerCAmelCase      ,)
  
  							__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 					UpperCamelCase	(     snake_case__      ):
  					__UpperCamelCase						=   """fine_acoustics"""
  
  
  
  
  					def __init__( self :					Union[str, Any]      ,_lowerCAmelCase :					List[str]=0.5      ,_lowerCAmelCase :					Tuple=512      ,_lowerCAmelCase :					List[str]=1_024      ,_lowerCAmelCase :					Optional[int]=8      ,**_lowerCAmelCase :					Optional[Any]      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(temperature=_lowerCAmelCase						)
  
  							__snake_case		       =     max_fine_history_length
  							__snake_case		       =     max_fine_input_length
  							__snake_case		       =     n_fine_codebooks
  
  
  
  
  class 					UpperCamelCase	(     snake_case__      ):
  					__UpperCamelCase						=   """bark"""
  					__UpperCamelCase						=   True
  
  
  
  
  					def __init__( self :					Optional[Any]      ,_lowerCAmelCase :					Dict = None      ,_lowerCAmelCase :					Dict = None      ,_lowerCAmelCase :					Dict = None      ,_lowerCAmelCase :					Tuple=24_000      ,_lowerCAmelCase :					List[str]=1_024      ,**_lowerCAmelCase :					Dict      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							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(**_lowerCAmelCase						)
  							__snake_case		       =     BarkCoarseGenerationConfig(**_lowerCAmelCase						)
  							__snake_case		       =     BarkFineGenerationConfig(**_lowerCAmelCase						)
  
  							__snake_case		       =     sample_rate
  							__snake_case		       =     codebook_size
  
  
  
  
  					@classmethod
  					def 							UpperCamelCase_						( cls :					List[Any]      ,_lowerCAmelCase :					BarkSemanticGenerationConfig      ,_lowerCAmelCase :					BarkCoarseGenerationConfig      ,_lowerCAmelCase :					BarkFineGenerationConfig      ,**_lowerCAmelCase :					List[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()      ,**_lowerCAmelCase      ,)
  
  
  
  
  
  
  
  					def 							UpperCamelCase_						( self :					Dict						):
  
  
  							"""simple docstring"""
  
  
  
  
  							__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
  
  
  
  
  
  
style_context: import os
  from shutil import copyfile
  from typing import Optional, Tuple
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import is_sentencepiece_available, logging
  
  
  if is_sentencepiece_available():
  		from .tokenization_reformer import ReformerTokenizer
  else:
  		lowerCamelCase__           =				None
  
  
  lowerCamelCase__           =				logging.get_logger(__name__)
  
  
  lowerCamelCase__           =				'▁'
  
  lowerCamelCase__           =				{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}
  
  lowerCamelCase__           =				{
      'vocab_file': {
          'google/reformer-crime-and-punishment': (
              'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
          )
      },
      'tokenizer_file': {
          'google/reformer-crime-and-punishment': (
              'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'
          )
      },
  }
  
  lowerCamelCase__           =				{
      'google/reformer-crime-and-punishment': 52_42_88,
  }
  
  
  
  
  class 					UpperCamelCase	(     snake_case__      ):
  					__UpperCamelCase						=   VOCAB_FILES_NAMES
  					__UpperCamelCase						=   PRETRAINED_VOCAB_FILES_MAP
  					__UpperCamelCase						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  					__UpperCamelCase						=   ["""input_ids""", """attention_mask"""]
  					__UpperCamelCase						=   ReformerTokenizer
  
  
  
  
  					def __init__( self :					Tuple      ,_lowerCAmelCase :					Dict=None      ,_lowerCAmelCase :					Union[str, Any]=None      ,_lowerCAmelCase :					int="</s>"      ,_lowerCAmelCase :					Dict="<unk>"      ,_lowerCAmelCase :					Dict=[]      ,**_lowerCAmelCase :					Optional[Any]      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(
  							    _lowerCAmelCase      ,tokenizer_file=_lowerCAmelCase      ,eos_token=_lowerCAmelCase      ,unk_token=_lowerCAmelCase      ,additional_special_tokens=_lowerCAmelCase      ,**_lowerCAmelCase      ,)
  
  							__snake_case		       =     vocab_file
  							__snake_case		       =     False if not self.vocab_file else True
  
  
  
  
  
  
  
  					def 							UpperCamelCase_						( self :					Dict      ,_lowerCAmelCase :					str      ,_lowerCAmelCase :					Optional[str] = None						):
  
  
  							"""simple docstring"""
  
  
  
  
  							if not self.can_save_slow_tokenizer:
  									raise ValueError(
  									    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
  									    "tokenizer."						)
  
  							if not os.path.isdir(_lowerCAmelCase						):
  									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""						)
  									return
  							__snake_case		       =     os.path.join(
  							    _lowerCAmelCase      ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
  
  							if os.path.abspath(self.vocab_file						) != os.path.abspath(_lowerCAmelCase						):
  									copyfile(self.vocab_file      ,_lowerCAmelCase						)
  
  							return (out_vocab_file,)
  
  
  
  
  
  