



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_nllb import NllbTokenizer
else:
			lowerCAmelCase__		:					List[Any]							=None


lowerCAmelCase__		:					Tuple							=logging.get_logger(__name__)


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

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

lowerCAmelCase__		:					Dict							={
    '''facebook/nllb-large-en-ro''': 1024,
    '''facebook/nllb-200-distilled-600M''': 1024,
}

# fmt: off
lowerCAmelCase__		:					Optional[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        UpperCAmelCase_  (       UpperCamelCase_	):

						'''simple docstring'''




						UpperCamelCase__      :			Dict      =  VOCAB_FILES_NAMES
						UpperCamelCase__      :			Dict      =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCamelCase__      :			Optional[Any]      =  PRETRAINED_VOCAB_FILES_MAP
						UpperCamelCase__      :			Optional[Any]      =  ['''input_ids''', '''attention_mask''']
						UpperCamelCase__      :			str      =  NllbTokenizer

						UpperCamelCase__      :			List[int]      =  []
						UpperCamelCase__      :			List[int]      =  []






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







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= AddedToken(_A				,							lstrip=_A				,							rstrip=_A		) if isinstance(_A				,							_A		) else mask_token
													__SCREAMING_SNAKE_CASE									= legacy_behaviour
													super().__init__(
													    vocab_file=_A				,							tokenizer_file=_A				,							bos_token=_A				,							eos_token=_A				,							sep_token=_A				,							cls_token=_A				,							unk_token=_A				,							pad_token=_A				,							mask_token=_A				,							src_lang=_A				,							tgt_lang=_A				,							additional_special_tokens=_A				,							legacy_behaviour=_A				,							**_A				,							)

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

													__SCREAMING_SNAKE_CASE									= 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}		)
													__SCREAMING_SNAKE_CASE									= {
													    lang_code: self.convert_tokens_to_ids(_A		) for lang_code in FAIRSEQ_LANGUAGE_CODES
													}

													__SCREAMING_SNAKE_CASE									= src_lang if src_lang is not None else 'eng_Latn'
													__SCREAMING_SNAKE_CASE									= self.convert_tokens_to_ids(self._src_lang		)
													__SCREAMING_SNAKE_CASE									= tgt_lang
													self.set_src_lang_special_tokens(self._src_lang		)






						@property
						def 	_A     (   self		):







													'''simple docstring'''

													return self._src_lang






						@src_lang.setter
						def 	_A     (   self				,							_A		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= new_src_lang
													self.set_src_lang_special_tokens(self._src_lang		)






						def 	_A     (   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 	_A     (   self				,							_A				,							_A = None		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= [self.sep_token_id]
													__SCREAMING_SNAKE_CASE									= [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 	_A     (   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'		)
													__SCREAMING_SNAKE_CASE									= src_lang
													__SCREAMING_SNAKE_CASE									= self(_A				,							add_special_tokens=_A				,							return_tensors=_A				,							**_A		)
													__SCREAMING_SNAKE_CASE									= self.convert_tokens_to_ids(_A		)
													__SCREAMING_SNAKE_CASE									= tgt_lang_id
													return inputs






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







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= src_lang
													__SCREAMING_SNAKE_CASE									= tgt_lang
													return super().prepare_seqaseq_batch(_A				,							_A				,							**_A		)






						def 	_A     (   self		):







													'''simple docstring'''

													return self.set_src_lang_special_tokens(self.src_lang		)






						def 	_A     (   self		):







													'''simple docstring'''

													return self.set_tgt_lang_special_tokens(self.tgt_lang		)






						def 	_A     (   self				,							_A		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= self.convert_tokens_to_ids(_A		)

													if self.legacy_behaviour:
																				__SCREAMING_SNAKE_CASE									= []
																				__SCREAMING_SNAKE_CASE									= [self.eos_token_id, self.cur_lang_code]
													else:
																				__SCREAMING_SNAKE_CASE									= [self.cur_lang_code]
																				__SCREAMING_SNAKE_CASE									= [self.eos_token_id]

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

													__SCREAMING_SNAKE_CASE									= 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 	_A     (   self				,							_A		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= self.convert_tokens_to_ids(_A		)
													if self.legacy_behaviour:
																				__SCREAMING_SNAKE_CASE									= []
																				__SCREAMING_SNAKE_CASE									= [self.eos_token_id, self.cur_lang_code]
													else:
																				__SCREAMING_SNAKE_CASE									= [self.cur_lang_code]
																				__SCREAMING_SNAKE_CASE									= [self.eos_token_id]

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

													__SCREAMING_SNAKE_CASE									= 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 	_A     (   self				,							_A				,							_A = None		):







													'''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(_A		):
																				logger.error(f"""Vocabulary path ({save_directory}) should be a directory."""		)
																				return
													__SCREAMING_SNAKE_CASE									= 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,)











import os






def      __lowercase       (			a__ = "input.txt"       )    ->			int:

							with open(os.path.join(os.path.dirname(a__       )							,       a__       )       ) as input_file:
														__SCREAMING_SNAKE_CASE									= [
														    [int(a__       ) for element in line.split(','       )]
														    for line in input_file.readlines()
														]

							__SCREAMING_SNAKE_CASE									= len(a__       )
							__SCREAMING_SNAKE_CASE									= len(matrix[0]       )

							__SCREAMING_SNAKE_CASE									= [[-1 for _ in range(a__       )] for _ in range(a__       )]
							for i in range(a__       ):
														__SCREAMING_SNAKE_CASE									= matrix[i][0]

							for j in range(1							,       a__       ):
														for i in range(a__       ):
																					__SCREAMING_SNAKE_CASE									= minimal_path_sums[i][j - 1] + matrix[i][j]

														for i in range(1							,       a__       ):
																					__SCREAMING_SNAKE_CASE									= min(
																					    minimal_path_sums[i][j]							,       minimal_path_sums[i - 1][j] + matrix[i][j]       )

														for i in range(rows - 2							,       -1							,       -1       ):
																					__SCREAMING_SNAKE_CASE									= min(
																					    minimal_path_sums[i][j]							,       minimal_path_sums[i + 1][j] + matrix[i][j]       )

							return min(minimal_path_sums_row[-1] for minimal_path_sums_row in minimal_path_sums       )


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






