"""simple docstring"""






import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase__						:						str		  =			logging.get_logger(__name__)

lowerCAmelCase__						:						int		  =			'▁'

lowerCAmelCase__						:						List[Any]		  =			{'vocab_file': 'sentencepiece.bpe.model'}

lowerCAmelCase__						:						List[Any]		  =			{
    'vocab_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'
        ),
    }
}

lowerCAmelCase__						:						Union[str, Any]		  =			{
    'facebook/nllb-200-distilled-600M': 1_024,
}

# fmt: off
lowerCAmelCase__						:						Union[str, Any]		  =			['ace_Arab', 'ace_Latn', 'acm_Arab', 'acq_Arab', 'aeb_Arab', 'afr_Latn', 'ajp_Arab', 'aka_Latn', 'amh_Ethi', 'apc_Arab', 'arb_Arab', 'ars_Arab', 'ary_Arab', 'arz_Arab', 'asm_Beng', 'ast_Latn', 'awa_Deva', 'ayr_Latn', 'azb_Arab', 'azj_Latn', 'bak_Cyrl', 'bam_Latn', 'ban_Latn', 'bel_Cyrl', 'bem_Latn', 'ben_Beng', 'bho_Deva', 'bjn_Arab', 'bjn_Latn', 'bod_Tibt', 'bos_Latn', 'bug_Latn', 'bul_Cyrl', 'cat_Latn', 'ceb_Latn', 'ces_Latn', 'cjk_Latn', 'ckb_Arab', 'crh_Latn', 'cym_Latn', 'dan_Latn', 'deu_Latn', 'dik_Latn', 'dyu_Latn', 'dzo_Tibt', 'ell_Grek', 'eng_Latn', 'epo_Latn', 'est_Latn', 'eus_Latn', 'ewe_Latn', 'fao_Latn', 'pes_Arab', 'fij_Latn', 'fin_Latn', 'fon_Latn', 'fra_Latn', 'fur_Latn', 'fuv_Latn', 'gla_Latn', 'gle_Latn', 'glg_Latn', 'grn_Latn', 'guj_Gujr', 'hat_Latn', 'hau_Latn', 'heb_Hebr', 'hin_Deva', 'hne_Deva', 'hrv_Latn', 'hun_Latn', 'hye_Armn', 'ibo_Latn', 'ilo_Latn', 'ind_Latn', 'isl_Latn', 'ita_Latn', 'jav_Latn', 'jpn_Jpan', 'kab_Latn', 'kac_Latn', 'kam_Latn', 'kan_Knda', 'kas_Arab', 'kas_Deva', 'kat_Geor', 'knc_Arab', 'knc_Latn', 'kaz_Cyrl', 'kbp_Latn', 'kea_Latn', 'khm_Khmr', 'kik_Latn', 'kin_Latn', 'kir_Cyrl', 'kmb_Latn', 'kon_Latn', 'kor_Hang', 'kmr_Latn', 'lao_Laoo', 'lvs_Latn', 'lij_Latn', 'lim_Latn', 'lin_Latn', 'lit_Latn', 'lmo_Latn', 'ltg_Latn', 'ltz_Latn', 'lua_Latn', 'lug_Latn', 'luo_Latn', 'lus_Latn', 'mag_Deva', 'mai_Deva', 'mal_Mlym', 'mar_Deva', 'min_Latn', 'mkd_Cyrl', 'plt_Latn', 'mlt_Latn', 'mni_Beng', 'khk_Cyrl', 'mos_Latn', 'mri_Latn', 'zsm_Latn', 'mya_Mymr', 'nld_Latn', 'nno_Latn', 'nob_Latn', 'npi_Deva', 'nso_Latn', 'nus_Latn', 'nya_Latn', 'oci_Latn', 'gaz_Latn', 'ory_Orya', 'pag_Latn', 'pan_Guru', 'pap_Latn', 'pol_Latn', 'por_Latn', 'prs_Arab', 'pbt_Arab', 'quy_Latn', 'ron_Latn', 'run_Latn', 'rus_Cyrl', 'sag_Latn', 'san_Deva', 'sat_Beng', 'scn_Latn', 'shn_Mymr', 'sin_Sinh', 'slk_Latn', 'slv_Latn', 'smo_Latn', 'sna_Latn', 'snd_Arab', 'som_Latn', 'sot_Latn', 'spa_Latn', 'als_Latn', 'srd_Latn', 'srp_Cyrl', 'ssw_Latn', 'sun_Latn', 'swe_Latn', 'swh_Latn', 'szl_Latn', 'tam_Taml', 'tat_Cyrl', 'tel_Telu', 'tgk_Cyrl', 'tgl_Latn', 'tha_Thai', 'tir_Ethi', 'taq_Latn', 'taq_Tfng', 'tpi_Latn', 'tsn_Latn', 'tso_Latn', 'tuk_Latn', 'tum_Latn', 'tur_Latn', 'twi_Latn', 'tzm_Tfng', 'uig_Arab', 'ukr_Cyrl', 'umb_Latn', 'urd_Arab', 'uzn_Latn', 'vec_Latn', 'vie_Latn', 'war_Latn', 'wol_Latn', 'xho_Latn', 'ydd_Hebr', 'yor_Latn', 'yue_Hant', 'zho_Hans', 'zho_Hant', 'zul_Latn']
class        snake_case (				__UpperCAmelCase       ):




					"""simple docstring"""

					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__       					=				[]
					snake_case__       					=				[]







					def __init__(       self     :			List[str]					,lowerCamelCase__     :			Tuple					,lowerCamelCase__     :			Optional[int]="<s>"					,lowerCamelCase__     :			Tuple="</s>"					,lowerCamelCase__     :			Dict="</s>"					,lowerCamelCase__     :			Optional[int]="<s>"					,lowerCamelCase__     :			Optional[Any]="<unk>"					,lowerCamelCase__     :			int="<pad>"					,lowerCamelCase__     :			Optional[Any]="<mask>"					,lowerCamelCase__     :			Optional[Any]=None					,lowerCamelCase__     :			Union[str, Any]=None					,lowerCamelCase__     :			Optional[Any]=None					,lowerCamelCase__     :			Optional[Dict[str, Any]] = None					,lowerCamelCase__     :			List[str]=None					,lowerCamelCase__     :			Any=False					,**lowerCamelCase__     :			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

									UpperCAmelCase__    =							{} if sp_model_kwargs is None else sp_model_kwargs
									UpperCAmelCase__    =							legacy_behaviour

									super().__init__(
									    bos_token=lowerCamelCase__					,eos_token=lowerCamelCase__					,unk_token=lowerCamelCase__					,sep_token=lowerCamelCase__					,cls_token=lowerCamelCase__					,pad_token=lowerCamelCase__					,mask_token=lowerCamelCase__					,tokenizer_file=lowerCamelCase__					,src_lang=lowerCamelCase__					,tgt_lang=lowerCamelCase__					,additional_special_tokens=lowerCamelCase__					,sp_model_kwargs=self.sp_model_kwargs					,legacy_behaviour=lowerCamelCase__					,**lowerCamelCase__					,)

									UpperCAmelCase__    =							spm.SentencePieceProcessor(**self.sp_model_kwargs    )
									self.sp_model.Load(str(lowerCamelCase__    )    )
									UpperCAmelCase__    =							vocab_file
									# Original fairseq vocab and spm vocab must be "aligned":
									# Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
									# -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
									# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
									# spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

									# Mimic fairseq token-to-id alignment for the first 4 token
									UpperCAmelCase__    =							{'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

									# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
									UpperCAmelCase__    =							1

									UpperCAmelCase__    =							len(self.sp_model    )
									UpperCAmelCase__    =							{
									    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowerCamelCase__    )
									}
									UpperCAmelCase__    =							{v: k for k, v in self.lang_code_to_id.items()}
									UpperCAmelCase__    =							len(self.sp_model    ) + len(self.lang_code_to_id    ) + self.fairseq_offset

									self.fairseq_tokens_to_ids.update(self.lang_code_to_id    )
									UpperCAmelCase__    =							{v: k for k, v in self.fairseq_tokens_to_ids.items()}
									UpperCAmelCase__    =							list(self.lang_code_to_id.keys()    )

									if additional_special_tokens is not None:
													# Only add those special tokens if they are not already there.
													self._additional_special_tokens.extend(
													    [t for t in additional_special_tokens if t not in self._additional_special_tokens]    )

									UpperCAmelCase__    =							src_lang if src_lang is not None else 'eng_Latn'
									UpperCAmelCase__    =							self.lang_code_to_id[self._src_lang]
									UpperCAmelCase__    =							tgt_lang
									self.set_src_lang_special_tokens(self._src_lang    )







					def __getstate__(       self     :			List[str]    ):
									UpperCAmelCase__    =							self.__dict__.copy()
									UpperCAmelCase__    =							None
									UpperCAmelCase__    =							self.sp_model.serialized_model_proto()
									return state







					def __setstate__(       self     :			int					,lowerCamelCase__     :			Tuple    ):
									UpperCAmelCase__    =							d

									# for backward compatibility
									if not hasattr(self					,'sp_model_kwargs'    ):
													UpperCAmelCase__    =							{}

									UpperCAmelCase__    =							spm.SentencePieceProcessor(**self.sp_model_kwargs    )
									self.sp_model.LoadFromSerializedProto(self.sp_model_proto    )







					@property
					def 	__lowerCAmelCase		(       self     :			Optional[Any]    ):
									return len(self.sp_model    ) + len(self.lang_code_to_id    ) + self.fairseq_offset + 1  # Plus 1 for the mask token







					@property
					def 	__lowerCAmelCase		(       self     :			str    ):
									return self._src_lang







					@src_lang.setter
					def 	__lowerCAmelCase		(       self     :			Dict					,lowerCamelCase__     :			str    ):
									UpperCAmelCase__    =							new_src_lang
									self.set_src_lang_special_tokens(self._src_lang    )







					def 	__lowerCAmelCase		(       self     :			str					,lowerCamelCase__     :			List[int]					,lowerCamelCase__     :			Optional[List[int]] = None					,lowerCamelCase__     :			bool = False    ):

									if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=lowerCamelCase__					,token_ids_a=lowerCamelCase__					,already_has_special_tokens=lowerCamelCase__    )

									UpperCAmelCase__    =							[1] * len(self.prefix_tokens    )
									UpperCAmelCase__    =							[1] * len(self.suffix_tokens    )
									if token_ids_a is None:
													return prefix_ones + ([0] * len(lowerCamelCase__    )) + suffix_ones
									return prefix_ones + ([0] * len(lowerCamelCase__    )) + ([0] * len(lowerCamelCase__    )) + suffix_ones







					def 	__lowerCAmelCase		(       self     :			Dict					,lowerCamelCase__     :			List[int]					,lowerCamelCase__     :			Optional[List[int]] = 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 	__lowerCAmelCase		(       self     :			Tuple					,lowerCamelCase__     :			List[int]					,lowerCamelCase__     :			Optional[List[int]] = None    ):
									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 	__lowerCAmelCase		(       self     :			Any					,lowerCamelCase__     :			Any					,lowerCamelCase__     :			str					,lowerCamelCase__     :			Optional[str]					,lowerCamelCase__     :			Optional[str]					,**lowerCamelCase__     :			Optional[int]    ):
									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 	__lowerCAmelCase		(       self     :			Any    ):
									UpperCAmelCase__    =							{self.convert_ids_to_tokens(lowerCamelCase__    ): i for i in range(self.vocab_size    )}
									vocab.update(self.added_tokens_encoder    )
									return vocab







					def 	__lowerCAmelCase		(       self     :			Union[str, Any]					,lowerCamelCase__     :			str    ):
									return self.sp_model.encode(lowerCamelCase__					,out_type=lowerCamelCase__    )







					def 	__lowerCAmelCase		(       self     :			List[str]					,lowerCamelCase__     :			Optional[int]    ):
									if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
									UpperCAmelCase__    =							self.sp_model.PieceToId(lowerCamelCase__    )

									# Need to return unknown token if the SP model returned 0
									return spm_id + self.fairseq_offset if spm_id else self.unk_token_id







					def 	__lowerCAmelCase		(       self     :			Optional[int]					,lowerCamelCase__     :			Dict    ):
									if index in self.fairseq_ids_to_tokens:
													return self.fairseq_ids_to_tokens[index]
									return self.sp_model.IdToPiece(index - self.fairseq_offset    )







					def 	__lowerCAmelCase		(       self     :			Any					,lowerCamelCase__     :			List[Any]    ):
									UpperCAmelCase__    =							''.join(lowerCamelCase__    ).replace(lowerCamelCase__					,' '    ).strip()
									return out_string







					def 	__lowerCAmelCase		(       self     :			Union[str, Any]					,lowerCamelCase__     :			str					,lowerCamelCase__     :			Optional[str] = None    ):
									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__    ) and os.path.isfile(self.vocab_file    ):
													copyfile(self.vocab_file					,lowerCamelCase__    )
									elif not os.path.isfile(self.vocab_file    ):
													with open(lowerCamelCase__					,'wb'    ) as fi:
																	UpperCAmelCase__    =							self.sp_model.serialized_model_proto()
																	fi.write(lowerCamelCase__    )

									return (out_vocab_file,)







					def 	__lowerCAmelCase		(       self     :			Optional[int]					,lowerCamelCase__     :			List[str]					,lowerCamelCase__     :			str = "eng_Latn"					,lowerCamelCase__     :			Optional[List[str]] = None					,lowerCamelCase__     :			str = "fra_Latn"					,**lowerCamelCase__     :			Tuple					,):
									UpperCAmelCase__    =							src_lang
									UpperCAmelCase__    =							tgt_lang
									return super().prepare_seqaseq_batch(lowerCamelCase__					,lowerCamelCase__					,**lowerCamelCase__    )







					def 	__lowerCAmelCase		(       self     :			str    ):
									return self.set_src_lang_special_tokens(self.src_lang    )







					def 	__lowerCAmelCase		(       self     :			List[Any]    ):
									return self.set_tgt_lang_special_tokens(self.tgt_lang    )







					def 	__lowerCAmelCase		(       self     :			Any					,lowerCamelCase__     :			Tuple    ):
									UpperCAmelCase__    =							self.lang_code_to_id[src_lang]
									if self.legacy_behaviour:
													UpperCAmelCase__    =							[]
													UpperCAmelCase__    =							[self.eos_token_id, self.cur_lang_code]
									else:
													UpperCAmelCase__    =							[self.cur_lang_code]
													UpperCAmelCase__    =							[self.eos_token_id]







					def 	__lowerCAmelCase		(       self     :			Union[str, Any]					,lowerCamelCase__     :			str    ):
									UpperCAmelCase__    =							self.lang_code_to_id[lang]
									if self.legacy_behaviour:
													UpperCAmelCase__    =							[]
													UpperCAmelCase__    =							[self.eos_token_id, self.cur_lang_code]
									else:
													UpperCAmelCase__    =							[self.cur_lang_code]
													UpperCAmelCase__    =							[self.eos_token_id]




"""simple docstring"""






def 						a_		(      lowerCamelCase      ,    lowerCamelCase ):
				return x if y == 0 else greatest_common_divisor(lowerCamelCase      ,    x % y )



def 						a_		(      lowerCamelCase      ,    lowerCamelCase ):
				return (x * y) // greatest_common_divisor(lowerCamelCase      ,    lowerCamelCase )



def 						a_		(      lowerCamelCase = 2_0 ):
				UpperCAmelCase__    =							1
				for i in range(1      ,    n + 1 ):
								UpperCAmelCase__    =							lcm(lowerCamelCase      ,    lowerCamelCase )
				return g


if __name__ == "__main__":
						print(F"""{solution() = }""")



