




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:
 a_ 		=  None


a_ 		=  logging.get_logger(__name__)

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

a_ 		=  {
    '''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'''
        ),
    },
}

a_ 		=  {
    '''facebook/mbart-large-50-one-to-many-mmt''': 1024,
}

# fmt: off
a_ 		=  ['''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    (      _SCREAMING_SNAKE_CASE ):

      """simple docstring"""

      lowerCAmelCase__      :			Optional[int]     =       VOCAB_FILES_NAMES
      lowerCAmelCase__      :			Tuple     =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCAmelCase__      :			Any     =       PRETRAINED_VOCAB_FILES_MAP
      lowerCAmelCase__      :			Optional[Any]     =       ["input_ids", "attention_mask"]
      lowerCAmelCase__      :			Any     =       MBartaaTokenizer

      lowerCAmelCase__      :			str     =       []
      lowerCAmelCase__      :			Tuple     =       []







      def __init__(  self       :			Optional[Any]			,							snake_case       :			Optional[int]=None			,							snake_case       :			Dict=None			,							snake_case       :			int=None			,							snake_case       :			str=None			,							snake_case       :			Optional[int]="</s>"			,							snake_case       :			Any="</s>"			,							snake_case       :			str="<s>"			,							snake_case       :			Optional[int]="<unk>"			,							snake_case       :			str="<pad>"			,							snake_case       :			List[Any]="<mask>"			,							**snake_case       :			Optional[Any]			,							):
          # 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

          __UpperCamelCase			=    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__(
              UpperCAmelCase_			,							src_lang=UpperCAmelCase_			,							tgt_lang=UpperCAmelCase_			,							tokenizer_file=UpperCAmelCase_			,							eos_token=UpperCAmelCase_			,							sep_token=UpperCAmelCase_			,							cls_token=UpperCAmelCase_			,							unk_token=UpperCAmelCase_			,							pad_token=UpperCAmelCase_			,							mask_token=UpperCAmelCase_			,							**UpperCAmelCase_			,							)

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

          __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			=    tgt_lang
          __UpperCamelCase			=    self.lang_code_to_id[self._src_lang]
          self.set_src_lang_special_tokens(self._src_lang					)







      @property
      def    snake_case						(  self       :			Tuple					):
          return self._src_lang







      @src_lang.setter
      def    snake_case						(  self       :			Tuple			,							snake_case       :			str					):
          __UpperCamelCase			=    new_src_lang
          self.set_src_lang_special_tokens(self._src_lang					)







      def    snake_case						(  self       :			int			,							snake_case       :			int			,							snake_case       :			List[Any] = None					):
          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    snake_case						(  self       :			Optional[int]			,							snake_case       :			Optional[int]			,							snake_case       :			List[str] = "en_XX"			,							snake_case       :			Tuple = None			,							snake_case       :			List[Any] = "ro_RO"			,							**snake_case       :			Union[str, Any]			,							):
          __UpperCamelCase			=    src_lang
          __UpperCamelCase			=    tgt_lang
          return super().prepare_seqaseq_batch(UpperCAmelCase_			,							UpperCAmelCase_			,							**UpperCAmelCase_					)







      def    snake_case						(  self       :			Union[str, Any]					):
          return self.set_src_lang_special_tokens(self.src_lang					)







      def    snake_case						(  self       :			Union[str, Any]					):
          return self.set_tgt_lang_special_tokens(self.tgt_lang					)







      def    snake_case						(  self       :			Tuple			,							snake_case       :			Optional[int]					):
          __UpperCamelCase			=    self.convert_tokens_to_ids(UpperCAmelCase_					)
          __UpperCamelCase			=    [self.cur_lang_code_id]
          __UpperCamelCase			=    [self.eos_token_id]

          __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    snake_case						(  self       :			Tuple			,							snake_case       :			List[str]					):
          __UpperCamelCase			=    self.convert_tokens_to_ids(UpperCAmelCase_					)
          __UpperCamelCase			=    [self.cur_lang_code_id]
          __UpperCamelCase			=    [self.eos_token_id]

          __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    snake_case						(  self       :			Optional[Any]			,							snake_case       :			str			,							snake_case       :			Optional[int]			,							snake_case       :			Any			,							snake_case       :			int			,							**snake_case       :			Optional[Any]					):
          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    snake_case						(  self       :			List[Any]			,							snake_case       :			Any			,							snake_case       :			Any = None					):
          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,)













def   _lowercase       (    _UpperCAmelCase					)    ->	bool:
				if not isinstance(_UpperCAmelCase      ,   _UpperCAmelCase					):
								lowerCamelCase									=F"""Input value of [number={number}] must be an integer"""
								raise TypeError(_UpperCAmelCase					)
				if number < 0 or number % 2 == 1:
								return False
				lowerCamelCase									=int(number**0.5					)
				return number == number_sqrt * (number_sqrt + 1)


if __name__ == "__main__":
							import doctest

							doctest.testmod()





