
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:
					SCREAMING_SNAKE_CASE							:int							 =				None


SCREAMING_SNAKE_CASE							:Optional[int]							 =				logging.get_logger(__name__)


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

SCREAMING_SNAKE_CASE							:List[Any]							 =				{
    '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'
        ),
    },
}

SCREAMING_SNAKE_CASE							:Optional[Any]							 =				{
    'facebook/nllb-large-en-ro': 1024,
    'facebook/nllb-200-distilled-600M': 1024,
}

# fmt: off
SCREAMING_SNAKE_CASE							: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      (  A_  ):




	'''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_					    =     NllbTokenizer

	snake_case_					    =     []
	snake_case_					    =     []






	def __init__(       self					: Union[str, Any]							,A					: Union[str, Any]=None							,A					: int=None							,A					: Any="<s>"							,A					: List[Any]="</s>"							,A					: List[str]="</s>"							,A					: Optional[int]="<s>"							,A					: str="<unk>"							,A					: List[Any]="<pad>"							,A					: int="<mask>"							,A					: int=None							,A					: Tuple=None							,A					: str=None							,A					: List[str]=False							,**A					: Optional[int]							,):
					__A   			= AddedToken(snake_case__							,lstrip=snake_case__							,rstrip=snake_case__ ) if isinstance(snake_case__							,snake_case__ ) else mask_token
					__A   			= legacy_behaviour
					super().__init__(
					    vocab_file=snake_case__							,tokenizer_file=snake_case__							,bos_token=snake_case__							,eos_token=snake_case__							,sep_token=snake_case__							,cls_token=snake_case__							,unk_token=snake_case__							,pad_token=snake_case__							,mask_token=snake_case__							,src_lang=snake_case__							,tgt_lang=snake_case__							,additional_special_tokens=snake_case__							,legacy_behaviour=snake_case__							,**snake_case__							,)

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

					__A   			= 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} )
					__A   			= {
					    lang_code: self.convert_tokens_to_ids(snake_case__ ) for lang_code in FAIRSEQ_LANGUAGE_CODES
					}

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






	@property
	def 				UpperCamelCase_  (       self					: List[Any] ):
					return self._src_lang






	@src_lang.setter
	def 				UpperCamelCase_  (       self					: int							,A					: str ):
					__A   			= new_src_lang
					self.set_src_lang_special_tokens(self._src_lang )






	def 				UpperCamelCase_  (       self					: List[str]							,A					: List[int]							,A					: 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 				UpperCamelCase_  (       self					: Optional[Any]							,A					: List[int]							,A					: Optional[List[int]] = None ):
					__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					: Optional[int]							,A					: Union[str, Any]							,A					: str							,A					: Optional[str]							,A					: Optional[str]							,**A					: str ):


					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(snake_case__							,add_special_tokens=snake_case__							,return_tensors=snake_case__							,**snake_case__ )
					__A   			= self.convert_tokens_to_ids(snake_case__ )
					__A   			= tgt_lang_id
					return inputs






	def 				UpperCamelCase_  (       self					: Union[str, Any]							,A					: List[str]							,A					: str = "eng_Latn"							,A					: Optional[List[str]] = None							,A					: str = "fra_Latn"							,**A					: List[str]							,):
					__A   			= src_lang
					__A   			= tgt_lang
					return super().prepare_seqaseq_batch(snake_case__							,snake_case__							,**snake_case__ )






	def 				UpperCamelCase_  (       self					: Dict ):
					return self.set_src_lang_special_tokens(self.src_lang )






	def 				UpperCamelCase_  (       self					: str ):
					return self.set_tgt_lang_special_tokens(self.tgt_lang )






	def 				UpperCamelCase_  (       self					: Optional[int]							,A					: List[Any] ):
					__A   			= self.convert_tokens_to_ids(snake_case__ )

					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]

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

					__A   			= 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					: int							,A					: str ):
					__A   			= self.convert_tokens_to_ids(snake_case__ )
					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]

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

					__A   			= 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					: int							,A					: str							,A					: Optional[str] = None ):


					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(snake_case__ ):
									logger.error(f'''Vocabulary path ({save_directory}) should be a directory.''' )
									return
					__A   			= 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__ ):
									copyfile(self.vocab_file							,snake_case__ )

					return (out_vocab_file,)


from __future__ import annotations

__lowerCamelCase							=       list[list[int]]

# assigning initial values to the grid
__lowerCamelCase							=       [
    [3, 0, 6, 5, 0, 8, 4, 0, 0],
    [5, 2, 0, 0, 0, 0, 0, 0, 0],
    [0, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]

# a grid with no solution
__lowerCamelCase							=       [
    [5, 0, 6, 5, 0, 8, 4, 0, 3],
    [5, 2, 0, 0, 0, 0, 0, 0, 2],
    [1, 8, 7, 0, 0, 0, 0, 3, 1],
    [0, 0, 3, 0, 1, 0, 0, 8, 0],
    [9, 0, 0, 8, 6, 3, 0, 0, 5],
    [0, 5, 0, 0, 9, 0, 6, 0, 0],
    [1, 3, 0, 0, 0, 0, 2, 5, 0],
    [0, 0, 0, 0, 0, 0, 0, 7, 4],
    [0, 0, 5, 2, 0, 6, 3, 0, 0],
]


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix				,					__lowerCamelCase     : int				,					__lowerCamelCase     : int				,					__lowerCamelCase     : int    ):
       for i in range(9    ):
              if grid[row][i] == n or grid[i][column] == n:
                     return False

       for i in range(3    ):
              for j in range(3    ):
                     if grid[(row - row % 3) + i][(column - column % 3) + j] == n:
                            return False

       return True


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix    ):
       for i in range(9    ):
              for j in range(9    ):
                     if grid[i][j] == 0:
                            return i, j
       return None


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix    ):
       if location := find_empty_location(__lowerCamelCase    ):
              snake_case				,					snake_case       :   Union[str, Any]							=      location
       else:
              # If the location is ``None``, then the grid is solved.
              return grid

       for digit in range(1				,					10    ):
              if is_safe(__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase				,					__lowerCamelCase    ):
                     snake_case       :   List[Any]							=      digit

                     if sudoku(__lowerCamelCase    ) is not None:
                            return grid

                     snake_case       :   Union[str, Any]							=      0

       return None


def 			UpperCamelCase					(    __lowerCamelCase     : Matrix    ):
       for row in grid:
              for cell in row:
                     print(__lowerCamelCase				,					end=" "    )
              print()


if __name__ == "__main__":
   # make a copy of grid so that you can compare with the unmodified grid
   for example_grid in (initial_grid, no_solution):
      print("""\nExample grid:\n""" + """=""" * 20)
      print_solution(example_grid)
      print("""\nExample grid solution:""")
      __lowerCamelCase							=       sudoku(example_grid)
      if solution is not None:
         print_solution(solution)
      else:
         print("""Cannot find a solution.""")





