





'''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


A__				:   List[Any]      =logging.get_logger(__name__)

A__				:   Any      ="""▁"""

A__				:   Dict      ={"""vocab_file""": """sentencepiece.bpe.model"""}

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

A__				:   str      ={
    """facebook/nllb-200-distilled-600M""": 10_24,
}

# fmt: off
A__				:   List[str]      =["""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  UpperCAmelCase     (			snake_case_   ):
      _lowercase:			Any						     =   VOCAB_FILES_NAMES
      _lowercase:			Tuple						     =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _lowercase:			Any						     =   PRETRAINED_VOCAB_FILES_MAP
      _lowercase:			List[str]						     =   ['''input_ids''', '''attention_mask''']

      _lowercase:			List[Any]						     =   []
      _lowercase:			List[Any]						     =   []




      def __init__(			self			: Optional[int]			,			__snake_case			: Optional[int]			,			__snake_case			: Any="<s>"			,			__snake_case			: Optional[Any]="</s>"			,			__snake_case			: Any="</s>"			,			__snake_case			: Union[str, Any]="<s>"			,			__snake_case			: Dict="<unk>"			,			__snake_case			: Tuple="<pad>"			,			__snake_case			: Any="<mask>"			,			__snake_case			: Union[str, Any]=None			,			__snake_case			: Any=None			,			__snake_case			: List[str]=None			,			__snake_case			: List[Any] = None			,			__snake_case			: Optional[int]=None			,			__snake_case			: Dict=False			,			**__snake_case			: Tuple			,			)				->      Optional[int]:
            _lowerCAmelCase							     =							AddedToken(__snake_case			,			lstrip=__snake_case			,			rstrip=__snake_case  ) if isinstance(__snake_case			,			__snake_case  ) else mask_token

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

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

            _lowerCAmelCase							     =							spm.SentencePieceProcessor(**self.sp_model_kwargs  )
            self.sp_model.Load(str(__snake_case  )  )
            _lowerCAmelCase							     =							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
            _lowerCAmelCase							     =							{"""<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
            _lowerCAmelCase							     =							1

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

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

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




      def __getstate__(			self			: Any  )				->      str:
            _lowerCAmelCase							     =							self.__dict__.copy()
            _lowerCAmelCase							     =							None
            _lowerCAmelCase							     =							self.sp_model.serialized_model_proto()
            return state




      def __setstate__(			self			: Dict			,			__snake_case			: Tuple  )				->      Dict:
            _lowerCAmelCase							     =							d

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

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




      @property
      def 				lowercase__    (			self			: Tuple  )				->      List[str]:
            return len(self.sp_model  ) + len(self.lang_code_to_id  ) + self.fairseq_offset + 1  # Plus 1 for the mask token




      @property
      def 				lowercase__    (			self			: Union[str, Any]  )				->      List[Any]:
            return self._src_lang




      @src_lang.setter
      def 				lowercase__    (			self			: List[Any]			,			__snake_case			: List[Any]  )				->      List[Any]:
            _lowerCAmelCase							     =							new_src_lang
            self.set_src_lang_special_tokens(self._src_lang  )




      def 				lowercase__    (			self			: Union[str, Any]			,			__snake_case			: Union[str, Any]			,			__snake_case			: List[str] = None			,			__snake_case			: int = False  )				->      Dict:

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

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




      def 				lowercase__    (			self			: Tuple			,			__snake_case			: str			,			__snake_case			: Tuple = None  )				->      List[str]:
            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 				lowercase__    (			self			: Optional[Any]			,			__snake_case			: str			,			__snake_case			: List[Any] = None  )				->      Union[str, Any]:
            _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 				lowercase__    (			self			: List[str]			,			__snake_case			: List[str]			,			__snake_case			: Optional[Any]			,			__snake_case			: str			,			__snake_case			: Optional[Any]			,			**__snake_case			: List[str]  )				->      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"""  )
            _lowerCAmelCase							     =							src_lang
            _lowerCAmelCase							     =							self(__snake_case			,			add_special_tokens=__snake_case			,			return_tensors=__snake_case			,			**__snake_case  )
            _lowerCAmelCase							     =							self.convert_tokens_to_ids(__snake_case  )
            _lowerCAmelCase							     =							tgt_lang_id
            return inputs




      def 				lowercase__    (			self			: Dict  )				->      Dict:
            _lowerCAmelCase							     =							{self.convert_ids_to_tokens(__snake_case  ): i for i in range(self.vocab_size  )}
            vocab.update(self.added_tokens_encoder  )
            return vocab




      def 				lowercase__    (			self			: Dict			,			__snake_case			: Optional[Any]  )				->      List[str]:
            return self.sp_model.encode(__snake_case			,			out_type=__snake_case  )




      def 				lowercase__    (			self			: Dict			,			__snake_case			: Any  )				->      Any:
            if token in self.fairseq_tokens_to_ids:
                  return self.fairseq_tokens_to_ids[token]
            _lowerCAmelCase							     =							self.sp_model.PieceToId(__snake_case  )

            # 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 				lowercase__    (			self			: Union[str, Any]			,			__snake_case			: int  )				->      int:
            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 				lowercase__    (			self			: Optional[Any]			,			__snake_case			: Optional[Any]  )				->      Optional[int]:
            _lowerCAmelCase							     =							"""""".join(__snake_case  ).replace(__snake_case			,			""" """  ).strip()
            return out_string




      def 				lowercase__    (			self			: Tuple			,			__snake_case			: Optional[int]			,			__snake_case			: List[str] = None  )				->      int:
            if not os.path.isdir(__snake_case  ):
                  logger.error(f"Vocabulary path ({save_directory}) should be a directory"  )
                  return
            _lowerCAmelCase							     =							os.path.join(
                __snake_case			,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )

            if os.path.abspath(self.vocab_file  ) != os.path.abspath(__snake_case  ) and os.path.isfile(self.vocab_file  ):
                  copyfile(self.vocab_file			,			__snake_case  )
            elif not os.path.isfile(self.vocab_file  ):
                  with open(__snake_case			,			"""wb"""  ) as fi:
                        _lowerCAmelCase							     =							self.sp_model.serialized_model_proto()
                        fi.write(__snake_case  )

            return (out_vocab_file,)




      def 				lowercase__    (			self			: Optional[int]			,			__snake_case			: Optional[Any]			,			__snake_case			: int = "eng_Latn"			,			__snake_case			: Union[str, Any] = None			,			__snake_case			: Dict = "fra_Latn"			,			**__snake_case			: Any			,			)				->      Dict:
            _lowerCAmelCase							     =							src_lang
            _lowerCAmelCase							     =							tgt_lang
            return super().prepare_seqaseq_batch(__snake_case			,			__snake_case			,			**__snake_case  )




      def 				lowercase__    (			self			: List[Any]  )				->      Optional[Any]:
            return self.set_src_lang_special_tokens(self.src_lang  )




      def 				lowercase__    (			self			: Tuple  )				->      List[str]:
            return self.set_tgt_lang_special_tokens(self.tgt_lang  )




      def 				lowercase__    (			self			: Any			,			__snake_case			: List[str]  )				->      Dict:
            _lowerCAmelCase							     =							self.lang_code_to_id[src_lang]
            if self.legacy_behaviour:
                  _lowerCAmelCase							     =							[]
                  _lowerCAmelCase							     =							[self.eos_token_id, self.cur_lang_code]
            else:
                  _lowerCAmelCase							     =							[self.cur_lang_code]
                  _lowerCAmelCase							     =							[self.eos_token_id]




      def 				lowercase__    (			self			: List[str]			,			__snake_case			: str  )				->      Optional[Any]:
            _lowerCAmelCase							     =							self.lang_code_to_id[lang]
            if self.legacy_behaviour:
                  _lowerCAmelCase							     =							[]
                  _lowerCAmelCase							     =							[self.eos_token_id, self.cur_lang_code]
            else:
                  _lowerCAmelCase							     =							[self.cur_lang_code]
                  _lowerCAmelCase							     =							[self.eos_token_id]










'''simple docstring'''

import os





def __snake_case					(      UpperCAmelCase_						:						str = "matrix.txt"		):
 with open(os.path.join(os.path.dirname(UpperCAmelCase_		)					,				UpperCAmelCase_		)		) as in_file:
  lowerCamelCase_      =  in_file.read()

 lowerCamelCase_      =  [[int(UpperCAmelCase_		) for cell in row.split(","		)] for row in data.strip().splitlines()]
 lowerCamelCase_      =  [[0 for cell in row] for row in grid]
 lowerCamelCase_      =  len(grid[0]		)

 lowerCamelCase_      =  [[0 for i in range(UpperCAmelCase_		)] for j in range(UpperCAmelCase_		)]
 lowerCamelCase_      =  grid[0][0]
 for i in range(1					,				UpperCAmelCase_		):
  lowerCamelCase_      =  grid[0][i] + dp[0][i - 1]
 for i in range(1					,				UpperCAmelCase_		):
  lowerCamelCase_      =  grid[i][0] + dp[i - 1][0]

 for i in range(1					,				UpperCAmelCase_		):
  for j in range(1					,				UpperCAmelCase_		):
   lowerCamelCase_      =  grid[i][j] + min(dp[i - 1][j]					,				dp[i][j - 1]		)

 return dp[-1][-1]


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



