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_mbart import MBartTokenizer
else:
  UpperCAmelCase_           =				None


UpperCAmelCase_           =				logging.get_logger(__name__)


UpperCAmelCase_           =				{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase_           =				{
    '''vocab_file''': {
        '''facebook/mbart-large-en-ro''': (
            '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'''
        ),
        '''facebook/mbart-large-cc25''': (
            '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/mbart-large-en-ro''': '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json''',
        '''facebook/mbart-large-cc25''': '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json''',
    },
}

UpperCAmelCase_           =				{
    '''facebook/mbart-large-en-ro''': 1_0_2_4,
    '''facebook/mbart-large-cc25''': 1_0_2_4,
}

# fmt: off
UpperCAmelCase_           =				['''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''']




class 			__magic_name__	(		__a     ):





   """simple docstring"""




   lowerCAmelCase   :     Optional[Any]	      = VOCAB_FILES_NAMES
   lowerCAmelCase   :     List[Any]	      = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCAmelCase   :     Tuple	      = PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase   :     int	      = ['''input_ids''', '''attention_mask''']
   lowerCAmelCase   :     int	      = MBartTokenizer

   lowerCAmelCase   :     List[int]	      = []
   lowerCAmelCase   :     List[int]	      = []



   def __init__(						self       :	str		,	_lowercase       :	Optional[int]=None		,	_lowercase       :	int=None		,	_lowercase       :	Tuple="<s>"		,	_lowercase       :	str="</s>"		,	_lowercase       :	Union[str, Any]="</s>"		,	_lowercase       :	Union[str, Any]="<s>"		,	_lowercase       :	Any="<unk>"		,	_lowercase       :	Optional[Any]="<pad>"		,	_lowercase       :	int="<mask>"		,	_lowercase       :	Optional[Any]=None		,	_lowercase       :	int=None		,	_lowercase       :	Optional[int]=None		,	**_lowercase       :	int		,	):



    """simple docstring"""



    _UpperCamelCase:  str    						=			AddedToken(_lowercase		,	lstrip=_lowercase		,	rstrip=_lowercase				) if isinstance(_lowercase		,	_lowercase				) else mask_token

    super().__init__(
        vocab_file=_lowercase		,	tokenizer_file=_lowercase		,	bos_token=_lowercase		,	eos_token=_lowercase		,	sep_token=_lowercase		,	cls_token=_lowercase		,	unk_token=_lowercase		,	pad_token=_lowercase		,	mask_token=_lowercase		,	src_lang=_lowercase		,	tgt_lang=_lowercase		,	additional_special_tokens=_lowercase		,	**_lowercase		,	)

    _UpperCamelCase:  List[Any]    						=			vocab_file
    _UpperCamelCase:  List[Any]    						=			False if not self.vocab_file else True

    _UpperCamelCase:  Any    						=			FAIRSEQ_LANGUAGE_CODES.copy()

    if additional_special_tokens is not None:
     # Only add those special tokens if they are not already there.
     _additional_special_tokens.extend(
         [t for t in additional_special_tokens if t not in _additional_special_tokens]				)

    self.add_special_tokens({'''additional_special_tokens''': _additional_special_tokens}				)
    _UpperCamelCase:  Tuple    						=			{
        lang_code: self.convert_tokens_to_ids(_lowercase				) for lang_code in FAIRSEQ_LANGUAGE_CODES
    }

    _UpperCamelCase:  Any    						=			src_lang if src_lang is not None else '''en_XX'''
    _UpperCamelCase:  List[str]    						=			self.convert_tokens_to_ids(self._src_lang				)
    _UpperCamelCase:  str    						=			tgt_lang
    self.set_src_lang_special_tokens(self._src_lang				)



   @property
   def 	lowerCAmelCase    (						self       :	Any				):



    """simple docstring"""



    return self._src_lang



   @src_lang.setter
   def 	lowerCAmelCase    (						self       :	str		,	_lowercase       :	str				):



    """simple docstring"""



    _UpperCamelCase:  int    						=			new_src_lang
    self.set_src_lang_special_tokens(self._src_lang				)



   def 	lowerCAmelCase    (						self       :	str		,	_lowercase       :	List[int]		,	_lowercase       :	Optional[List[int]] = None				):



    """simple docstring"""



    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       :	List[Any]		,	_lowercase       :	List[int]		,	_lowercase       :	Optional[List[int]] = None				):



    """simple docstring"""



    _UpperCamelCase:  Union[str, Any]    						=			[self.sep_token_id]
    _UpperCamelCase:  Union[str, Any]    						=			[self.cls_token_id]

    if token_ids_a is None:
     return len(cls + token_ids_a + sep				) * [0]
    return len(cls + token_ids_a + sep + sep + token_ids_a + sep				) * [0]



   def 	lowerCAmelCase    (						self       :	List[str]		,	_lowercase       :	Tuple		,	_lowercase       :	str		,	_lowercase       :	Optional[str]		,	_lowercase       :	Optional[str]		,	**_lowercase       :	Any				):



    """simple docstring"""



    if src_lang is None or tgt_lang is None:
     raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model'''				)
    _UpperCamelCase:  Tuple    						=			src_lang
    _UpperCamelCase:  int    						=			self(_lowercase		,	add_special_tokens=_lowercase		,	return_tensors=_lowercase		,	**_lowercase				)
    _UpperCamelCase:  Optional[Any]    						=			self.convert_tokens_to_ids(_lowercase				)
    _UpperCamelCase:  Any    						=			tgt_lang_id
    return inputs



   def 	lowerCAmelCase    (						self       :	int		,	_lowercase       :	List[str]		,	_lowercase       :	str = "en_XX"		,	_lowercase       :	Optional[List[str]] = None		,	_lowercase       :	str = "ro_RO"		,	**_lowercase       :	Optional[Any]		,	):



    """simple docstring"""



    _UpperCamelCase:  Any    						=			src_lang
    _UpperCamelCase:  List[str]    						=			tgt_lang
    return super().prepare_seqaseq_batch(_lowercase		,	_lowercase		,	**_lowercase				)



   def 	lowerCAmelCase    (						self       :	List[str]				):



    """simple docstring"""



    return self.set_src_lang_special_tokens(self.src_lang				)



   def 	lowerCAmelCase    (						self       :	str				):



    """simple docstring"""



    return self.set_tgt_lang_special_tokens(self.tgt_lang				)



   def 	lowerCAmelCase    (						self       :	List[Any]		,	_lowercase       :	Dict				):



    """simple docstring"""



    _UpperCamelCase:  int    						=			self.convert_tokens_to_ids(_lowercase				)
    _UpperCamelCase:  Tuple    						=			[]
    _UpperCamelCase:  str    						=			[self.eos_token_id, self.cur_lang_code]

    _UpperCamelCase:  Optional[Any]    						=			self.convert_ids_to_tokens(self.prefix_tokens				)
    _UpperCamelCase:  Dict    						=			self.convert_ids_to_tokens(self.suffix_tokens				)

    _UpperCamelCase:  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       :	Tuple		,	_lowercase       :	str				):



    """simple docstring"""



    _UpperCamelCase:  Optional[int]    						=			self.convert_tokens_to_ids(_lowercase				)
    _UpperCamelCase:  Optional[int]    						=			[]
    _UpperCamelCase:  List[Any]    						=			[self.eos_token_id, self.cur_lang_code]

    _UpperCamelCase:  List[str]    						=			self.convert_ids_to_tokens(self.prefix_tokens				)
    _UpperCamelCase:  Any    						=			self.convert_ids_to_tokens(self.suffix_tokens				)

    _UpperCamelCase:  Dict    						=			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       :	Union[str, Any]		,	_lowercase       :	str		,	_lowercase       :	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(_lowercase				):
     logger.error(f"""Vocabulary path ({save_directory}) should be a directory."""				)
     return
    _UpperCamelCase:  Union[str, Any]    						=			os.path.join(
        _lowercase		,	(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)

    if os.path.abspath(self.vocab_file				) != os.path.abspath(_lowercase				):
     copyfile(self.vocab_file		,	_lowercase				)

    return (out_vocab_file,)
import random




def    lowerCAmelCase_  (		lowercase:				int	,       lowercase:				float	,       lowercase:				bool = False		)     ->					dict:







 '''simple docstring'''
 _UpperCamelCase:  dict    						=			{i: [] for i in range(lowercase		)}

 # if probability is greater or equal than 1, then generate a complete graph
 if probability >= 1:
  return complete_graph(lowercase		)
 # if probability is lower or equal than 0, then return a graph without edges
 if probability <= 0:
  return graph

 # for each couple of nodes, add an edge from u to v
 # if the number randomly generated is greater than probability probability
 for i in range(lowercase		):
  for j in range(i + 1	,       lowercase		):
   if random.random() < probability:
    graph[i].append(lowercase		)
    if not directed:
     # if the graph is undirected, add an edge in from j to i, either
     graph[j].append(lowercase		)
 return graph




def    lowerCAmelCase_  (		lowercase:				int		)     ->					dict:







 '''simple docstring'''
 return {
     i: [j for j in range(lowercase		) if i != j] for i in range(lowercase		)
 }


if __name__ == "__main__":
  import doctest

  doctest.testmod()