






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:
	a_							=    None


a_							=    logging.get_logger(__name__)


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

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

a_							=    {
    '''facebook/mbart-large-en-ro''': 1024,
    '''facebook/mbart-large-cc25''': 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''']


class      lowercase__     (			_UpperCAmelCase	):
	a_         =VOCAB_FILES_NAMES
	a_         =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	a_         =PRETRAINED_VOCAB_FILES_MAP
	a_         =["""input_ids""", """attention_mask"""]
	a_         =MBartTokenizer

	a_         =[]
	a_         =[]

	def __init__(							self		,    __UpperCAmelCase=None		,    __UpperCAmelCase=None		,    __UpperCAmelCase="<s>"		,    __UpperCAmelCase="</s>"		,    __UpperCAmelCase="</s>"		,    __UpperCAmelCase="<s>"		,    __UpperCAmelCase="<unk>"		,    __UpperCAmelCase="<pad>"		,    __UpperCAmelCase="<mask>"		,    __UpperCAmelCase=None		,    __UpperCAmelCase=None		,    __UpperCAmelCase=None		,    **__UpperCAmelCase		,    )->					int:







							'''simple docstring'''





							lowerCAmelCase__       =						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		,    )

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

							lowerCAmelCase__       =						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}       )
							lowerCAmelCase__       =						{
							    lang_code: self.convert_tokens_to_ids(__UpperCAmelCase       ) for lang_code in FAIRSEQ_LANGUAGE_CODES
							}

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

	@property
	def 		UpperCAmelCase  (							self       )->					str:







							'''simple docstring'''





							return self._src_lang

	@src_lang.setter
	def 		UpperCAmelCase  (							self		,    __UpperCAmelCase       )->					None:







							'''simple docstring'''





							lowerCAmelCase__       =						new_src_lang
							self.set_src_lang_special_tokens(self._src_lang       )

	def 		UpperCAmelCase  (							self		,    __UpperCAmelCase		,    __UpperCAmelCase = None       )->					List[int]:







							'''simple docstring'''





							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		,    __UpperCAmelCase		,    __UpperCAmelCase = None       )->					List[int]:







							'''simple docstring'''





							lowerCAmelCase__       =						[self.sep_token_id]
							lowerCAmelCase__       =						[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		,    __UpperCAmelCase		,    __UpperCAmelCase		,    __UpperCAmelCase		,    __UpperCAmelCase		,    **__UpperCAmelCase       )->					Optional[Any]:







							'''simple docstring'''





							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(__UpperCAmelCase		,    add_special_tokens=__UpperCAmelCase		,    return_tensors=__UpperCAmelCase		,    **__UpperCAmelCase       )
							lowerCAmelCase__       =						self.convert_tokens_to_ids(__UpperCAmelCase       )
							lowerCAmelCase__       =						tgt_lang_id
							return inputs

	def 		UpperCAmelCase  (							self		,    __UpperCAmelCase		,    __UpperCAmelCase = "en_XX"		,    __UpperCAmelCase = None		,    __UpperCAmelCase = "ro_RO"		,    **__UpperCAmelCase		,    )->					BatchEncoding:







							'''simple docstring'''





							lowerCAmelCase__       =						src_lang
							lowerCAmelCase__       =						tgt_lang
							return super().prepare_seqaseq_batch(__UpperCAmelCase		,    __UpperCAmelCase		,    **__UpperCAmelCase       )

	def 		UpperCAmelCase  (							self       )->					Optional[int]:







							'''simple docstring'''





							return self.set_src_lang_special_tokens(self.src_lang       )

	def 		UpperCAmelCase  (							self       )->					Union[str, Any]:







							'''simple docstring'''





							return self.set_tgt_lang_special_tokens(self.tgt_lang       )

	def 		UpperCAmelCase  (							self		,    __UpperCAmelCase       )->					None:







							'''simple docstring'''





							lowerCAmelCase__       =						self.convert_tokens_to_ids(__UpperCAmelCase       )
							lowerCAmelCase__       =						[]
							lowerCAmelCase__       =						[self.eos_token_id, self.cur_lang_code]

							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 		UpperCAmelCase  (							self		,    __UpperCAmelCase       )->					None:







							'''simple docstring'''





							lowerCAmelCase__       =						self.convert_tokens_to_ids(__UpperCAmelCase       )
							lowerCAmelCase__       =						[]
							lowerCAmelCase__       =						[self.eos_token_id, self.cur_lang_code]

							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 		UpperCAmelCase  (							self		,    __UpperCAmelCase		,    __UpperCAmelCase = None       )->					Tuple[str]:







							'''simple docstring'''





							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
							lowerCAmelCase__       =						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,)














from __future__ import annotations

from collections.abc import Generator


def        _a  (     ) ->   Generator[int, None, None]:
						"""simple docstring"""







						lowerCAmelCase__       =						{}
						lowerCAmelCase__       =						2
						while True:
												lowerCAmelCase__       =						factor_map.pop(UpperCamelCase_    ,   UpperCamelCase_   )
												if factor:
																		lowerCAmelCase__       =						factor + prime
																		while x in factor_map:
																								x += factor
																		lowerCAmelCase__       =						factor
												else:
																		lowerCAmelCase__       =						prime
																		yield prime
												prime += 1


def        _a  (     UpperCamelCase_					:				float = 1e1_0   ) ->   int:
						"""simple docstring"""







						lowerCAmelCase__       =						sieve()

						lowerCAmelCase__       =						1
						while True:
												lowerCAmelCase__       =						next(UpperCamelCase_   )
												if (2 * prime * n) > limit:
																		return n
												# Ignore the next prime as the reminder will be 2.
												next(UpperCamelCase_   )
												n += 2


if __name__ == "__main__":
	print(solution())






