






"""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


SCREAMING_SNAKE_CASE						:						Dict					   =       logging.get_logger(__name__)

SCREAMING_SNAKE_CASE						:						Union[str, Any]					   =       '''▁'''

SCREAMING_SNAKE_CASE						:						str					   =       {'''vocab_file''': '''sentencepiece.bpe.model'''}

SCREAMING_SNAKE_CASE						:						Dict					   =       {
    '''vocab_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'''
        ),
    }
}

SCREAMING_SNAKE_CASE						:						Optional[Any]					   =       {
    '''facebook/nllb-200-distilled-600M''': 1_024,
}

# fmt: off
SCREAMING_SNAKE_CASE						:						Optional[int]					   =       ['''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_       (    _lowerCamelCase       ):



	"""simple docstring"""

	SCREAMING_SNAKE_CASE_:							Optional[Any]   			=					VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE_:							Optional[Any]   			=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	SCREAMING_SNAKE_CASE_:							int   			=					PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE_:							List[str]   			=					["""input_ids""", """attention_mask"""]

	SCREAMING_SNAKE_CASE_:							List[int]   			=					[]
	SCREAMING_SNAKE_CASE_:							List[int]   			=					[]


	def __init__(      self  ,					__a  ,					__a="<s>"  ,					__a="</s>"  ,					__a="</s>"  ,					__a="<s>"  ,					__a="<unk>"  ,					__a="<pad>"  ,					__a="<mask>"  ,					__a=None  ,					__a=None  ,					__a=None  ,					__a = None  ,					__a=None  ,					__a=False  ,					**__a  ,					):


					"""simple docstring"""

					A__							 =       AddedToken(__a  ,					lstrip=__a  ,					rstrip=__a						) if isinstance(__a  ,					__a						) else mask_token

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

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

					A__							 =       spm.SentencePieceProcessor(**self.sp_model_kwargs						)
					self.sp_model.Load(str(__a						)						)
					A__							 =       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
					A__							 =       {'<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
					A__							 =       1

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

					self.fairseq_tokens_to_ids.update(self.lang_code_to_id						)
					A__							 =       {v: k for k, v in self.fairseq_tokens_to_ids.items()}
					A__							 =       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]						)

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


	def __getstate__(      self						):


					"""simple docstring"""

					A__							 =       self.__dict__.copy()
					A__							 =       None
					A__							 =       self.sp_model.serialized_model_proto()
					return state


	def __setstate__(      self  ,					__a						):


					"""simple docstring"""

					A__							 =       d

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

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


	@property
	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					return len(self.sp_model						) + len(self.lang_code_to_id						) + self.fairseq_offset + 1  # Plus 1 for the mask token


	@property
	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					return self._src_lang


	@src_lang.setter
	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					A__							 =       new_src_lang
					self.set_src_lang_special_tokens(self._src_lang						)


	def       _UpperCAmelCase						(      self  ,					__a  ,					__a = None  ,					__a = False						):


					"""simple docstring"""

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

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


	def       _UpperCAmelCase						(      self  ,					__a  ,					__a = None						):


					"""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  ,					__a  ,					__a = None						):


					"""simple docstring"""

					A__							 =       [self.sep_token_id]
					A__							 =       [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  ,					__a  ,					__a  ,					__a  ,					__a  ,					**__a						):


					"""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'						)
					A__							 =       src_lang
					A__							 =       self(__a  ,					add_special_tokens=__a  ,					return_tensors=__a  ,					**__a						)
					A__							 =       self.convert_tokens_to_ids(__a						)
					A__							 =       tgt_lang_id
					return inputs


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       {self.convert_ids_to_tokens(__a						): i for i in range(self.vocab_size						)}
					vocab.update(self.added_tokens_encoder						)
					return vocab


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					return self.sp_model.encode(__a  ,					out_type=__a						)


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					if token in self.fairseq_tokens_to_ids:
									return self.fairseq_tokens_to_ids[token]
					A__							 =       self.sp_model.PieceToId(__a						)

					# 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       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					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       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					A__							 =       ''.join(__a						).replace(__a  ,					' '						).strip()
					return out_string


	def       _UpperCAmelCase						(      self  ,					__a  ,					__a = None						):


					"""simple docstring"""

					if not os.path.isdir(__a						):
									logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''						)
									return
					A__							 =       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						) and os.path.isfile(self.vocab_file						):
									copyfile(self.vocab_file  ,					__a						)
					elif not os.path.isfile(self.vocab_file						):
									with open(__a  ,					'wb'						) as fi:
													A__							 =       self.sp_model.serialized_model_proto()
													fi.write(__a						)

					return (out_vocab_file,)


	def       _UpperCAmelCase						(      self  ,					__a  ,					__a = "eng_Latn"  ,					__a = None  ,					__a = "fra_Latn"  ,					**__a  ,					):


					"""simple docstring"""

					A__							 =       src_lang
					A__							 =       tgt_lang
					return super().prepare_seqaseq_batch(__a  ,					__a  ,					**__a						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					return self.set_src_lang_special_tokens(self.src_lang						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					return self.set_tgt_lang_special_tokens(self.tgt_lang						)


	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					A__							 =       self.lang_code_to_id[src_lang]
					if self.legacy_behaviour:
									A__							 =       []
									A__							 =       [self.eos_token_id, self.cur_lang_code]
					else:
									A__							 =       [self.cur_lang_code]
									A__							 =       [self.eos_token_id]






	def       _UpperCAmelCase						(      self  ,					__a						):


					"""simple docstring"""

					A__							 =       self.lang_code_to_id[lang]
					if self.legacy_behaviour:
									A__							 =       []
									A__							 =       [self.eos_token_id, self.cur_lang_code]
					else:
									A__							 =       [self.cur_lang_code]
									A__							 =       [self.eos_token_id]










"""simple docstring"""






from maths.prime_check import is_prime



def  __lowerCamelCase					(					lowerCAmelCase__				):
				if not isinstance(lowerCAmelCase__       ,lowerCAmelCase__				):
								A__							 =       f'''Input value of [number={number}] must be an integer'''
								raise TypeError(lowerCAmelCase__				)
				if is_prime(lowerCAmelCase__				) and is_prime(number + 2				):
								return number + 2
				else:
								return -1


if __name__ == "__main__":
					import doctest

					doctest.testmod()


