code: 
  
  
  '''simple docstring'''
  
  import os
  from shutil import copyfile
  from typing import List, Optional, Tuple
  
  from tokenizers import processors
  
  from ...tokenization_utils import AddedToken, BatchEncoding
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import is_sentencepiece_available, logging
  
  
  if is_sentencepiece_available():
  							from .tokenization_mbartaa import MBartaaTokenizer
  else:
  							lowerCAmelCase   :Union[str, Any]								=    None
  
  
  lowerCAmelCase   :str								=    logging.get_logger(__name__)
  
  lowerCAmelCase   :Optional[int]								=    {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}
  
  lowerCAmelCase   :Any								=    {
      '''vocab_file''': {
          '''facebook/mbart-large-50-one-to-many-mmt''': (
              '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model'''
          ),
      },
      '''tokenizer_file''': {
          '''facebook/mbart-large-50-one-to-many-mmt''': (
              '''https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/tokenizer.json'''
          ),
      },
  }
  
  lowerCAmelCase   :Optional[int]								=    {
      '''facebook/mbart-large-50-one-to-many-mmt''': 1_0_2_4,
  }
  
  # fmt: off
  lowerCAmelCase   :Dict								=    ['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''', '''af_ZA''', '''az_AZ''', '''bn_IN''', '''fa_IR''', '''he_IL''', '''hr_HR''', '''id_ID''', '''ka_GE''', '''km_KH''', '''mk_MK''', '''ml_IN''', '''mn_MN''', '''mr_IN''', '''pl_PL''', '''ps_AF''', '''pt_XX''', '''sv_SE''', '''sw_KE''', '''ta_IN''', '''te_IN''', '''th_TH''', '''tl_XX''', '''uk_UA''', '''ur_PK''', '''xh_ZA''', '''gl_ES''', '''sl_SI''']
  class _lowerCamelCase (		lowercase__							):
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		A_			:    int   					=       VOCAB_FILES_NAMES
  		A_			:    Tuple   					=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  		A_			:    Dict   					=       PRETRAINED_VOCAB_FILES_MAP
  		A_			:    Union[str, Any]   					=       ["""input_ids""", """attention_mask"""]
  		A_			:    Optional[Any]   					=       MBartaaTokenizer
  
  		A_			:    List[int]   					=       []
  		A_			:    List[int]   					=       []
  
  
  
  
  
  
  
  		def __init__(      self	:		Optional[int]						,  _A	:		Any=None						,  _A	:		Union[str, Any]=None						,  _A	:		List[Any]=None						,  _A	:		Union[str, Any]=None						,  _A	:		Optional[Any]="</s>"						,  _A	:		Union[str, Any]="</s>"						,  _A	:		str="<s>"						,  _A	:		Tuple="<unk>"						,  _A	:		Union[str, Any]="<pad>"						,  _A	:		Any="<mask>"						,  **_A	:		List[str]						,  )						->				Dict:
  			# Mask token behave like a normal word, i.e. include the space before it
  			__magic_name__ :					int  			=  AddedToken(_A						,  lstrip=_A						,  rstrip=_A    ) if isinstance(_A						,  _A    ) else mask_token
  
  			__magic_name__ :					Optional[Any]  			=  kwargs.get('additional_special_tokens'						,  []    )
  			kwargs["additional_special_tokens"] += [
  			    code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
  			]
  
  			super().__init__(
  			    _A						,  src_lang=_A						,  tgt_lang=_A						,  tokenizer_file=_A						,  eos_token=_A						,  sep_token=_A						,  cls_token=_A						,  unk_token=_A						,  pad_token=_A						,  mask_token=_A						,  **_A						,  )
  
  			__magic_name__ :					Optional[Any]  			=  vocab_file
  			__magic_name__ :					List[Any]  			=  False if not self.vocab_file else True
  
  			__magic_name__ :					Union[str, Any]  			=  {
  			    lang_code: self.convert_tokens_to_ids(_A    ) for lang_code in FAIRSEQ_LANGUAGE_CODES
  			}
  
  			__magic_name__ :					Any  			=  src_lang if src_lang is not None else 'en_XX'
  			__magic_name__ :					Dict  			=  tgt_lang
  			__magic_name__ :					Dict  			=  self.lang_code_to_id[self._src_lang]
  			self.set_src_lang_special_tokens(self._src_lang    )
  
  
  
  
  
  
  
  		@property
  		def      __lowerCAmelCase	(      self	:		Any    )						->				str:
  			return self._src_lang
  
  
  
  
  
  
  
  		@src_lang.setter
  		def      __lowerCAmelCase	(      self	:		List[str]						,  _A	:		str    )						->				None:
  			__magic_name__ :					List[str]  			=  new_src_lang
  			self.set_src_lang_special_tokens(self._src_lang    )
  
  
  
  
  
  
  
  		def      __lowerCAmelCase	(      self	:		Tuple						,  _A	:		List[int]						,  _A	:		Optional[List[int]] = None    )						->				List[int]:
  			if token_ids_a is None:
  				return self.prefix_tokens + token_ids_a + self.suffix_tokens
  			# We don't expect to process pairs, but leave the pair logic for API consistency
  			return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens
  
  
  
  
  
  
  
  		def      __lowerCAmelCase	(      self	:		str						,  _A	:		List[str]						,  _A	:		str = "en_XX"						,  _A	:		Optional[List[str]] = None						,  _A	:		str = "ro_RO"						,  **_A	:		Tuple						,  )						->				BatchEncoding:
  			__magic_name__ :					List[str]  			=  src_lang
  			__magic_name__ :					Optional[int]  			=  tgt_lang
  			return super().prepare_seqaseq_batch(_A						,  _A						,  **_A    )
  
  
  
  
  
  
  
  		def      __lowerCAmelCase	(      self	:		List[str]    )						->				List[str]:
  			return self.set_src_lang_special_tokens(self.src_lang    )
  
  
  
  
  
  
  
  		def      __lowerCAmelCase	(      self	:		Tuple    )						->				Dict:
  			return self.set_tgt_lang_special_tokens(self.tgt_lang    )
  
  
  
  
  
  
  
  		def      __lowerCAmelCase	(      self	:		str						,  _A	:		str    )						->				None:
  			__magic_name__ :					Optional[Any]  			=  self.convert_tokens_to_ids(_A    )
  			__magic_name__ :					Optional[Any]  			=  [self.cur_lang_code_id]
  			__magic_name__ :					List[Any]  			=  [self.eos_token_id]
  
  			__magic_name__ :					int  			=  self.convert_ids_to_tokens(self.prefix_tokens    )
  			__magic_name__ :					Optional[Any]  			=  self.convert_ids_to_tokens(self.suffix_tokens    )
  
  			__magic_name__ :					Tuple  			=  processors.TemplateProcessing(
  			    single=prefix_tokens_str + ['$A'] + suffix_tokens_str						,  pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str						,  special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str						,  self.prefix_tokens + self.suffix_tokens    )    )						,  )
  
  
  
  
  
  
  
  		def      __lowerCAmelCase	(      self	:		Optional[int]						,  _A	:		str    )						->				None:
  			__magic_name__ :					Any  			=  self.convert_tokens_to_ids(_A    )
  			__magic_name__ :					List[Any]  			=  [self.cur_lang_code_id]
  			__magic_name__ :					Dict  			=  [self.eos_token_id]
  
  			__magic_name__ :					Dict  			=  self.convert_ids_to_tokens(self.prefix_tokens    )
  			__magic_name__ :					Union[str, Any]  			=  self.convert_ids_to_tokens(self.suffix_tokens    )
  
  			__magic_name__ :					Optional[int]  			=  processors.TemplateProcessing(
  			    single=prefix_tokens_str + ['$A'] + suffix_tokens_str						,  pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str						,  special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str						,  self.prefix_tokens + self.suffix_tokens    )    )						,  )
  
  
  
  
  
  
  
  		def      __lowerCAmelCase	(      self	:		Any						,  _A	:		Dict						,  _A	:		str						,  _A	:		Optional[str]						,  _A	:		Optional[str]						,  **_A	:		Optional[Any]    )						->				Tuple:
  			if src_lang is None or tgt_lang is None:
  				raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'    )
  			__magic_name__ :					List[Any]  			=  src_lang
  			__magic_name__ :					str  			=  self(_A						,  add_special_tokens=_A						,  return_tensors=_A						,  **_A    )
  			__magic_name__ :					Tuple  			=  self.convert_tokens_to_ids(_A    )
  			__magic_name__ :					Optional[Any]  			=  tgt_lang_id
  			return inputs
  
  
  
  
  
  
  
  		def      __lowerCAmelCase	(      self	:		Dict						,  _A	:		str						,  _A	:		Optional[str] = None    )						->				Tuple[str]:
  			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(_A    ):
  				logger.error(F'Vocabulary path ({save_directory}) should be a directory'    )
  				return
  			__magic_name__ :					Union[str, Any]  			=  os.path.join(
  			    _A						,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )
  
  			if os.path.abspath(self.vocab_file    ) != os.path.abspath(_A    ):
  				copyfile(self.vocab_file						,  _A    )
  
  			return (out_vocab_file,)
style_context: 
  
  
  '''simple docstring'''
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowerCAmelCase   :List[Any]								=    logging.get_logger(__name__)
  
  lowerCAmelCase   :Dict								=    {
      '''uw-madison/yoso-4096''': '''https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json''',
      # See all YOSO models at https://huggingface.co/models?filter=yoso
  }
  class _lowerCamelCase (		lowercase__							):
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		A_			:    Optional[Any]   					=       """yoso"""
  
  
  
  
  
  
  
  		def __init__(      self	:		Any						,  _A	:		List[Any]=50265						,  _A	:		Any=768						,  _A	:		List[str]=12						,  _A	:		Dict=12						,  _A	:		Union[str, Any]=3072						,  _A	:		List[Any]="gelu"						,  _A	:		Dict=0.1						,  _A	:		Union[str, Any]=0.1						,  _A	:		Union[str, Any]=4096						,  _A	:		Dict=1						,  _A	:		Tuple=0.02						,  _A	:		Any=1E-12						,  _A	:		Optional[int]="absolute"						,  _A	:		Tuple=True						,  _A	:		Any=9						,  _A	:		Tuple=64						,  _A	:		str=None						,  _A	:		Dict=True						,  _A	:		str=True						,  _A	:		int=1						,  _A	:		Optional[int]=0						,  _A	:		Tuple=2						,  **_A	:		Optional[Any]						,  )						->				Any:
  			super().__init__(pad_token_id=_A						,  bos_token_id=_A						,  eos_token_id=_A						,  **_A    )
  
  			__magic_name__ :					List[Any]  			=  vocab_size
  			__magic_name__ :					int  			=  max_position_embeddings
  			__magic_name__ :					int  			=  hidden_size
  			__magic_name__ :					Any  			=  num_hidden_layers
  			__magic_name__ :					List[str]  			=  num_attention_heads
  			__magic_name__ :					str  			=  intermediate_size
  			__magic_name__ :					Any  			=  hidden_act
  			__magic_name__ :					Union[str, Any]  			=  hidden_dropout_prob
  			__magic_name__ :					str  			=  attention_probs_dropout_prob
  			__magic_name__ :					int  			=  initializer_range
  			__magic_name__ :					List[Any]  			=  type_vocab_size
  			__magic_name__ :					Tuple  			=  layer_norm_eps
  			__magic_name__ :					Tuple  			=  position_embedding_type
  			__magic_name__ :					Optional[Any]  			=  use_expectation
  			__magic_name__ :					Union[str, Any]  			=  hash_code_len
  			__magic_name__ :					int  			=  num_hash
  			__magic_name__ :					List[Any]  			=  conv_window
  			__magic_name__ :					Optional[Any]  			=  use_fast_hash
  			__magic_name__ :					int  			=  lsh_backward