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:
 UpperCAmelCase     						=			None


UpperCAmelCase     						=			logging.get_logger(__name__)

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

UpperCAmelCase     						=			{
    '''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'''
        ),
    },
}

UpperCAmelCase     						=			{
    '''facebook/mbart-large-50-one-to-many-mmt''': 10_24,
}

# 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''', '''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					(    a_  ):



 '''simple docstring'''
 _lowerCamelCase  :		Optional[int]			      =	VOCAB_FILES_NAMES
 _lowerCamelCase  :		int			      =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCamelCase  :		Dict			      =	PRETRAINED_VOCAB_FILES_MAP
 _lowerCamelCase  :		Optional[Any]			      =	['input_ids', 'attention_mask']
 _lowerCamelCase  :		int			      =	MBartaaTokenizer

 _lowerCamelCase  :		List[int]			      =	[]
 _lowerCamelCase  :		List[int]			      =	[]

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

        _UpperCamelCase       :    List[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__(
            lowerCamelCase    ,     src_lang=lowerCamelCase    ,     tgt_lang=lowerCamelCase    ,     tokenizer_file=lowerCamelCase    ,     eos_token=lowerCamelCase    ,     sep_token=lowerCamelCase    ,     cls_token=lowerCamelCase    ,     unk_token=lowerCamelCase    ,     pad_token=lowerCamelCase    ,     mask_token=lowerCamelCase    ,     **lowerCamelCase    ,     )

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

        _UpperCamelCase       :    Union[str, Any]					  =					{
            lang_code: self.convert_tokens_to_ids(lowerCamelCase					) for lang_code in FAIRSEQ_LANGUAGE_CODES
        }

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

 @property
 def    __snake_case   (     self    :						List[Any]					)	->							str:
        return self._src_lang

 @src_lang.setter
 def    __snake_case   (     self    :						Optional[Any]    ,     lowerCamelCase    :						str					)	->							None:
        _UpperCamelCase       :    Optional[Any]					  =					new_src_lang
        self.set_src_lang_special_tokens(self._src_lang					)

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

 def    __snake_case   (     self    :						Optional[int]					)	->							Any:
        return self.set_src_lang_special_tokens(self.src_lang					)

 def    __snake_case   (     self    :						Tuple					)	->							int:
        return self.set_tgt_lang_special_tokens(self.tgt_lang					)

 def    __snake_case   (     self    :						List[Any]    ,     lowerCamelCase    :						str					)	->							None:
        _UpperCamelCase       :    int					  =					self.convert_tokens_to_ids(lowerCamelCase					)
        _UpperCamelCase       :    Dict					  =					[self.cur_lang_code_id]
        _UpperCamelCase       :    Optional[Any]					  =					[self.eos_token_id]

        _UpperCamelCase       :    Tuple					  =					self.convert_ids_to_tokens(self.prefix_tokens					)
        _UpperCamelCase       :    Any					  =					self.convert_ids_to_tokens(self.suffix_tokens					)

        _UpperCamelCase       :    Optional[Any]					  =					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    :						int    ,     lowerCamelCase    :						str					)	->							None:
        _UpperCamelCase       :    List[Any]					  =					self.convert_tokens_to_ids(lowerCamelCase					)
        _UpperCamelCase       :    Optional[int]					  =					[self.cur_lang_code_id]
        _UpperCamelCase       :    str					  =					[self.eos_token_id]

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

        _UpperCamelCase       :    List[str]					  =					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[int]    ,     lowerCamelCase    :						Dict    ,     lowerCamelCase    :						str    ,     lowerCamelCase    :						Optional[str]    ,     lowerCamelCase    :						Optional[str]    ,     **lowerCamelCase    :						Optional[int]					)	->							Dict:
        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       :    Dict					  =					src_lang
        _UpperCamelCase       :    List[Any]					  =					self(lowerCamelCase    ,     add_special_tokens=lowerCamelCase    ,     return_tensors=lowerCamelCase    ,     **lowerCamelCase					)
        _UpperCamelCase       :    Dict					  =					self.convert_tokens_to_ids(lowerCamelCase					)
        _UpperCamelCase       :    List[Any]					  =					tgt_lang_id
        return inputs

 def    __snake_case   (     self    :						Union[str, Any]    ,     lowerCamelCase    :						str    ,     lowerCamelCase    :						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(lowerCamelCase					):
               logger.error(f"Vocabulary path ({save_directory}) should be a directory"					)
               return
        _UpperCamelCase       :    List[str]					  =					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,)




def SCREAMING_SNAKE_CASE			(       lowercase_:		int			):
       if not isinstance(lowercase_						,  lowercase_			):
              _UpperCamelCase       :    Optional[int]					  =					(
                  'operation can not be conducted on a object of type '
                  F"{type(lowercase_			).__name__}"
              )
              raise TypeError(lowercase_			)
       _UpperCamelCase       :    List[Any]					  =					''
       for _ in range(0						,  32			):
              bit_string += str(number % 2			)
              _UpperCamelCase       :    Dict					  =					number >> 1
       return bit_string


def SCREAMING_SNAKE_CASE			(       lowercase_:		int			):
       if number < 0:
              raise ValueError('the value of input must be positive'			)
       elif isinstance(lowercase_						,  lowercase_			):
              raise TypeError('Input value must be a \'int\' type'			)
       elif isinstance(lowercase_						,  lowercase_			):
              raise TypeError('\'<\' not supported between instances of \'str\' and \'int\''			)
       _UpperCamelCase       :    List[Any]					  =					0
       # iterator over [1 to 32],since we are dealing with 32 bit integer
       for _ in range(1						,  33			):
              # left shift the bits by unity
              _UpperCamelCase       :    Tuple					  =					result << 1
              # get the end bit
              _UpperCamelCase       :    List[Any]					  =					number % 2
              # right shift the bits by unity
              _UpperCamelCase       :    Dict					  =					number >> 1
              # add that bit to our ans
              _UpperCamelCase       :    int					  =					result | end_bit
       return get_reverse_bit_string(lowercase_			)


if __name__ == "__main__":
 import doctest

 doctest.testmod()



