"""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:
		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_024,
    'facebook/mbart-large-cc25': 1_024,
}

# 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      UpperCAmelCase_       (						UpperCamelCase__):
							snake_case__        =      VOCAB_FILES_NAMES
							snake_case__        =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							snake_case__        =      PRETRAINED_VOCAB_FILES_MAP
							snake_case__        =      ['''input_ids''', '''attention_mask''']
							snake_case__        =      MBartTokenizer

							snake_case__        =      []
							snake_case__        =      []






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

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

												_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(__lowerCamelCase  ) 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 :      List[str]  )       ->       List[str]:
												return self._src_lang






							@src_lang.setter
							def       _UpperCamelCase			(		self :      Tuple     ,						__UpperCamelCase :      List[Any]  )       ->       str:
												_UpperCamelCase      						=	new_src_lang
												self.set_src_lang_special_tokens(self._src_lang  )






							def       _UpperCamelCase			(		self :      Dict     ,						__UpperCamelCase :      Optional[Any]     ,						__UpperCamelCase :      str = None  )       ->       Tuple:
												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 :      List[str]     ,						__UpperCamelCase :      int     ,						__UpperCamelCase :      str = None  )       ->       str:
												_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 :      int     ,						__UpperCamelCase :      Optional[Any]     ,						__UpperCamelCase :      str     ,						__UpperCamelCase :      Dict     ,						__UpperCamelCase :      List[Any]     ,						**__UpperCamelCase :      Optional[int]  )       ->       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(__lowerCamelCase     ,						add_special_tokens=__lowerCamelCase     ,						return_tensors=__lowerCamelCase     ,						**__lowerCamelCase  )
												_UpperCamelCase      						=	self.convert_tokens_to_ids(__lowerCamelCase  )
												_UpperCamelCase      						=	tgt_lang_id
												return inputs






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






							def       _UpperCamelCase			(		self :      Union[str, Any]  )       ->       int:
												return self.set_src_lang_special_tokens(self.src_lang  )






							def       _UpperCamelCase			(		self :      Optional[int]  )       ->       Tuple:
												return self.set_tgt_lang_special_tokens(self.tgt_lang  )






							def       _UpperCamelCase			(		self :      Optional[Any]     ,						__UpperCamelCase :      Tuple  )       ->       int:
												_UpperCamelCase      						=	self.convert_tokens_to_ids(__lowerCamelCase  )
												_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 :      Dict     ,						__UpperCamelCase :      Dict  )       ->       Dict:
												_UpperCamelCase      						=	self.convert_tokens_to_ids(__lowerCamelCase  )
												_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[int]     ,						__UpperCamelCase :      Union[str, Any]     ,						__UpperCamelCase :      Tuple = None  )       ->       Optional[int]:
												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      						=	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,)







from ..utils import DummyObject, requires_backends




class     SCREAMING_SNAKE_CASE__ (						metaclass=UpperCamelCase__      ):
 __SCREAMING_SNAKE_CASE							       =	['''keras_nlp''']



 def __init__(							self,*__lowerCamelCase,**__lowerCamelCase ):
        requires_backends(self,['''keras_nlp'''] )





