



'''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_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': 1024,
}

# 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 __snake_case(      _UpperCamelCase					):


						'''simple docstring'''



						UpperCAmelCase							:    Tuple           =		VOCAB_FILES_NAMES
						UpperCAmelCase							:    List[Any]           =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCAmelCase							:    Union[str, Any]           =		PRETRAINED_VOCAB_FILES_MAP
						UpperCAmelCase							:    int           =		["input_ids", "attention_mask"]
						UpperCAmelCase							:    Dict           =		MBartaaTokenizer

						UpperCAmelCase							:    List[int]           =		[]
						UpperCAmelCase							:    List[int]           =		[]


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

							lowerCAmelCase    =	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__(
							    __a	,       src_lang=__a	,       tgt_lang=__a	,       tokenizer_file=__a	,       eos_token=__a	,       sep_token=__a	,       cls_token=__a	,       unk_token=__a	,       pad_token=__a	,       mask_token=__a	,       **__a	,       )

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

							lowerCAmelCase    =	{
							    lang_code: self.convert_tokens_to_ids(__a      ) for lang_code in FAIRSEQ_LANGUAGE_CODES
							}

							lowerCAmelCase    =	src_lang if src_lang is not None else "en_XX"
							lowerCAmelCase    =	tgt_lang
							lowerCAmelCase    =	self.lang_code_to_id[self._src_lang]
							self.set_src_lang_special_tokens(self._src_lang      )


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


						@src_lang.setter
						def 				__snake_case    (					self	,       A_      )	->	None:
							lowerCAmelCase    =	new_src_lang
							self.set_src_lang_special_tokens(self._src_lang      )


						def 				__snake_case    (					self	,       A_	,       A_ = 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	,       A_	,       A_ = "en_XX"	,       A_ = None	,       A_ = "ro_RO"	,       **A_	,       )	->	BatchEncoding:
							lowerCAmelCase    =	src_lang
							lowerCAmelCase    =	tgt_lang
							return super().prepare_seqaseq_batch(__a	,       __a	,       **__a      )


						def 				__snake_case    (					self      )	->	int:
							return self.set_src_lang_special_tokens(self.src_lang      )


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


						def 				__snake_case    (					self	,       A_      )	->	None:
							lowerCAmelCase    =	self.convert_tokens_to_ids(__a      )
							lowerCAmelCase    =	[self.cur_lang_code_id]
							lowerCAmelCase    =	[self.eos_token_id]

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

							lowerCAmelCase    =	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	,       A_      )	->	None:
							lowerCAmelCase    =	self.convert_tokens_to_ids(__a      )
							lowerCAmelCase    =	[self.cur_lang_code_id]
							lowerCAmelCase    =	[self.eos_token_id]

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

							lowerCAmelCase    =	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	,       A_	,       A_	,       A_	,       A_	,       **A_      )	->	List[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"""      )
							lowerCAmelCase    =	src_lang
							lowerCAmelCase    =	self(__a	,       add_special_tokens=__a	,       return_tensors=__a	,       **__a      )
							lowerCAmelCase    =	self.convert_tokens_to_ids(__a      )
							lowerCAmelCase    =	tgt_lang_id
							return inputs




						def 				__snake_case    (					self	,       A_	,       A_ = 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(__a      ):
								logger.error(f'Vocabulary path ({save_directory}) should be a directory'      )
								return
							lowerCAmelCase    =	os.path.join(
							    __a	,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )

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

							return (out_vocab_file,)






"""simple docstring"""


def     lowercase__			(    lowercase_	)    ->						str:




      """simple docstring"""

      return " ".join(sorted(set(sentence.split()	)	)	)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
