





'''simple docstring'''






import random
from typing import Any


def 					_a   (__SCREAMING_SNAKE_CASE   ):


		"""simple docstring"""

		for _ in range(len(__SCREAMING_SNAKE_CASE   )   ):
				_UpperCamelCase       			=random.randint(0  ,      len(__SCREAMING_SNAKE_CASE   ) - 1   )
				_UpperCamelCase       			=random.randint(0  ,      len(__SCREAMING_SNAKE_CASE   ) - 1   )
				_UpperCamelCase			,     _UpperCamelCase       			=data[b], data[a]
		return data


if __name__ == "__main__":
						__lowerCamelCase						: Optional[int]		=   [0, 1, 2, 3, 4, 5, 6, 7]
						__lowerCamelCase						: Union[str, Any]		=   ['''python''', '''says''', '''hello''', '''!''']
						print('Fisher-Yates Shuffle:')
						print('List', integers, strings)
						print('FY Shuffle', fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))













'''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_mbart import MBartTokenizer
else:
      __lowerCamelCase						: List[Any]		=   None


__lowerCamelCase						: Optional[int]		=   logging.get_logger(__name__)


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

__lowerCamelCase						: Union[str, Any]		=   {
    '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',
    },
}

__lowerCamelCase						: List[str]		=   {
    'facebook/mbart-large-en-ro': 1024,
    'facebook/mbart-large-cc25': 1024,
}

# fmt: off
__lowerCamelCase						: Optional[int]		=   ['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 		UpperCAmelCase   (				lowercase_):


  """simple docstring"""







  lowerCAmelCase_					=				VOCAB_FILES_NAMES
  lowerCAmelCase_					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowerCAmelCase_					=				PRETRAINED_VOCAB_FILES_MAP
  lowerCAmelCase_					=				["""input_ids""", """attention_mask"""]
  lowerCAmelCase_					=				MBartTokenizer

  lowerCAmelCase_					=				[]
  lowerCAmelCase_					=				[]


  def __init__(				self    :					Optional[int]							,	UpperCamelCase__    :					List[Any]=None							,	UpperCamelCase__    :					Tuple=None							,	UpperCamelCase__    :					List[str]="<s>"							,	UpperCamelCase__    :					Optional[Any]="</s>"							,	UpperCamelCase__    :					Dict="</s>"							,	UpperCamelCase__    :					str="<s>"							,	UpperCamelCase__    :					Tuple="<unk>"							,	UpperCamelCase__    :					Dict="<pad>"							,	UpperCamelCase__    :					str="<mask>"							,	UpperCamelCase__    :					Any=None							,	UpperCamelCase__    :					List[str]=None							,	UpperCamelCase__    :					Dict=None							,	**UpperCamelCase__    :					Any							,	)     ->						List[str]:
    # Mask token behave like a normal word, i.e. include the space before it
    _UpperCamelCase       			=AddedToken(UpperCamelCase__							,	lstrip=UpperCamelCase__							,	rstrip=UpperCamelCase__  ) if isinstance(UpperCamelCase__							,	UpperCamelCase__  ) else mask_token

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

    _UpperCamelCase       			=vocab_file
    _UpperCamelCase       			=False if not self.vocab_file else True

    _UpperCamelCase       			=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       			={
        lang_code: self.convert_tokens_to_ids(UpperCamelCase__  ) for lang_code in FAIRSEQ_LANGUAGE_CODES
    }

    _UpperCamelCase       			=src_lang if src_lang is not None else '''en_XX'''
    _UpperCamelCase       			=self.convert_tokens_to_ids(self._src_lang  )
    _UpperCamelCase       			=tgt_lang
    self.set_src_lang_special_tokens(self._src_lang  )


  @property
  def   UpperCamelCase__      (				self    :					str  )     ->						str:
    return self._src_lang


  @src_lang.setter
  def   UpperCamelCase__      (				self    :					List[str]							,	UpperCamelCase__    :					str  )     ->						None:
    _UpperCamelCase       			=new_src_lang
    self.set_src_lang_special_tokens(self._src_lang  )


  def   UpperCamelCase__      (				self    :					Dict							,	UpperCamelCase__    :					List[int]							,	UpperCamelCase__    :					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   UpperCamelCase__      (				self    :					Dict							,	UpperCamelCase__    :					List[int]							,	UpperCamelCase__    :					Optional[List[int]] = None  )     ->						List[int]:
    _UpperCamelCase       			=[self.sep_token_id]
    _UpperCamelCase       			=[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   UpperCamelCase__      (				self    :					str							,	UpperCamelCase__    :					Optional[int]							,	UpperCamelCase__    :					str							,	UpperCamelCase__    :					Optional[str]							,	UpperCamelCase__    :					Optional[str]							,	**UpperCamelCase__    :					List[str]  )     ->						str:
    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       			=src_lang
    _UpperCamelCase       			=self(UpperCamelCase__							,	add_special_tokens=UpperCamelCase__							,	return_tensors=UpperCamelCase__							,	**UpperCamelCase__  )
    _UpperCamelCase       			=self.convert_tokens_to_ids(UpperCamelCase__  )
    _UpperCamelCase       			=tgt_lang_id
    return inputs


  def   UpperCamelCase__      (				self    :					Union[str, Any]							,	UpperCamelCase__    :					List[str]							,	UpperCamelCase__    :					str = "en_XX"							,	UpperCamelCase__    :					Optional[List[str]] = None							,	UpperCamelCase__    :					str = "ro_RO"							,	**UpperCamelCase__    :					Optional[int]							,	)     ->						BatchEncoding:
    _UpperCamelCase       			=src_lang
    _UpperCamelCase       			=tgt_lang
    return super().prepare_seqaseq_batch(UpperCamelCase__							,	UpperCamelCase__							,	**UpperCamelCase__  )


  def   UpperCamelCase__      (				self    :					Tuple  )     ->						List[str]:
    return self.set_src_lang_special_tokens(self.src_lang  )


  def   UpperCamelCase__      (				self    :					Union[str, Any]  )     ->						List[str]:
    return self.set_tgt_lang_special_tokens(self.tgt_lang  )


  def   UpperCamelCase__      (				self    :					str							,	UpperCamelCase__    :					str  )     ->						None:
    _UpperCamelCase       			=self.convert_tokens_to_ids(UpperCamelCase__  )
    _UpperCamelCase       			=[]
    _UpperCamelCase       			=[self.eos_token_id, self.cur_lang_code]

    _UpperCamelCase       			=self.convert_ids_to_tokens(self.prefix_tokens  )
    _UpperCamelCase       			=self.convert_ids_to_tokens(self.suffix_tokens  )

    _UpperCamelCase       			=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   UpperCamelCase__      (				self    :					str							,	UpperCamelCase__    :					str  )     ->						None:
    _UpperCamelCase       			=self.convert_tokens_to_ids(UpperCamelCase__  )
    _UpperCamelCase       			=[]
    _UpperCamelCase       			=[self.eos_token_id, self.cur_lang_code]

    _UpperCamelCase       			=self.convert_ids_to_tokens(self.prefix_tokens  )
    _UpperCamelCase       			=self.convert_ids_to_tokens(self.suffix_tokens  )

    _UpperCamelCase       			=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   UpperCamelCase__      (				self    :					Optional[Any]							,	UpperCamelCase__    :					str							,	UpperCamelCase__    :					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(UpperCamelCase__  ):
      logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''  )
      return
    _UpperCamelCase       			=os.path.join(
        UpperCamelCase__							,	(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )

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

    return (out_vocab_file,)






