




'''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


UpperCAmelCase_							:	Tuple	     =		logging.get_logger(__name__)

UpperCAmelCase_							:	Tuple	     =		'''▁'''

UpperCAmelCase_							:	Optional[int]	     =		{'''vocab_file''': '''sentencepiece.bpe.model'''}

UpperCAmelCase_							:	Tuple	     =		{
    '''vocab_file''': {
        '''facebook/mbart-large-en-ro''': (
            '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'''
        ),
        '''facebook/mbart-large-cc25''': (
            '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'''
        ),
    }
}

UpperCAmelCase_							:	str	     =		{
    '''facebook/mbart-large-en-ro''': 1_0_2_4,
    '''facebook/mbart-large-cc25''': 1_0_2_4,
}

# fmt: off
UpperCAmelCase_							:	Any	     =		['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''']





class      lowerCAmelCase (			__lowerCAmelCase):
       __lowercase	:   int										=      VOCAB_FILES_NAMES
       __lowercase	:   List[Any]										=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __lowercase	:   int										=      PRETRAINED_VOCAB_FILES_MAP
       __lowercase	:   List[str]										=      ['''input_ids''', '''attention_mask''']

       __lowercase	:   List[int]										=      []
       __lowercase	:   List[int]										=      []


       def __init__( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE="<s>"     ,	__SCREAMING_SNAKE_CASE="</s>"     ,	__SCREAMING_SNAKE_CASE="</s>"     ,	__SCREAMING_SNAKE_CASE="<s>"     ,	__SCREAMING_SNAKE_CASE="<unk>"     ,	__SCREAMING_SNAKE_CASE="<pad>"     ,	__SCREAMING_SNAKE_CASE="<mask>"     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE = None     ,	__SCREAMING_SNAKE_CASE=None     ,	**__SCREAMING_SNAKE_CASE     ,	)   ->	int:



            '''simple docstring'''




            __snake_case            =	AddedToken(__SCREAMING_SNAKE_CASE     ,	lstrip=__SCREAMING_SNAKE_CASE     ,	rstrip=__SCREAMING_SNAKE_CASE	) if isinstance(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE	) else mask_token

            __snake_case            =	{} if sp_model_kwargs is None else sp_model_kwargs

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

            __snake_case            =	spm.SentencePieceProcessor(**self.sp_model_kwargs	)
            self.sp_model.Load(str(__SCREAMING_SNAKE_CASE	)	)
            __snake_case            =	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>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
            # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

            # Mimic fairseq token-to-id alignment for the first 4 token
            __snake_case            =	{'''<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
            __snake_case            =	1

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

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

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


       def __getstate__( self	)   ->	int:



            '''simple docstring'''




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


       def __setstate__( self     ,	__SCREAMING_SNAKE_CASE	)   ->	Any:



            '''simple docstring'''




            __snake_case            =	d

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

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


       @property
       def    lowerCAmelCase   ( self	)   ->	int:



            '''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    lowerCAmelCase   ( self	)   ->	str:



            '''simple docstring'''




            return self._src_lang


       @src_lang.setter
       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	None:



            '''simple docstring'''




            __snake_case            =	new_src_lang
            self.set_src_lang_special_tokens(self._src_lang	)


       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE = None     ,	__SCREAMING_SNAKE_CASE = False	)   ->	List[int]:



            '''simple docstring'''




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

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


       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE = None	)   ->	List[int]:



            '''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    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE = None	)   ->	List[int]:



            '''simple docstring'''




            __snake_case            =	[self.sep_token_id]
            __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    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	**__SCREAMING_SNAKE_CASE	)   ->	Optional[Any]:



            '''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'''	)
            __snake_case            =	src_lang
            __snake_case            =	self(__SCREAMING_SNAKE_CASE     ,	add_special_tokens=__SCREAMING_SNAKE_CASE     ,	return_tensors=__SCREAMING_SNAKE_CASE     ,	**__SCREAMING_SNAKE_CASE	)
            __snake_case            =	self.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE	)
            __snake_case            =	tgt_lang_id
            return inputs


       def    lowerCAmelCase   ( self	)   ->	Any:



            '''simple docstring'''




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


       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	List[str]:



            '''simple docstring'''




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


       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	List[str]:



            '''simple docstring'''




            if token in self.fairseq_tokens_to_ids:
                 return self.fairseq_tokens_to_ids[token]
            __snake_case            =	self.sp_model.PieceToId(__SCREAMING_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    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	List[Any]:



            '''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    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	List[Any]:



            '''simple docstring'''




            __snake_case            =	''''''.join(__SCREAMING_SNAKE_CASE	).replace(__SCREAMING_SNAKE_CASE     ,	''' '''	).strip()
            return out_string


       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE = None	)   ->	Tuple[str]:



            '''simple docstring'''




            if not os.path.isdir(__SCREAMING_SNAKE_CASE	):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''	)
                 return
            __snake_case            =	os.path.join(
                __SCREAMING_SNAKE_CASE     ,	(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']	)

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

            return (out_vocab_file,)


       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE = "en_XX"     ,	__SCREAMING_SNAKE_CASE = None     ,	__SCREAMING_SNAKE_CASE = "ro_RO"     ,	**__SCREAMING_SNAKE_CASE     ,	)   ->	BatchEncoding:



            '''simple docstring'''




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


       def    lowerCAmelCase   ( self	)   ->	Dict:



            '''simple docstring'''




            return self.set_src_lang_special_tokens(self.src_lang	)


       def    lowerCAmelCase   ( self	)   ->	Dict:



            '''simple docstring'''




            return self.set_tgt_lang_special_tokens(self.tgt_lang	)


       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	None:



            '''simple docstring'''




            __snake_case            =	self.lang_code_to_id[src_lang]
            __snake_case            =	[]
            __snake_case            =	[self.eos_token_id, self.cur_lang_code]




       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	None:



            '''simple docstring'''




            __snake_case            =	self.lang_code_to_id[lang]
            __snake_case            =	[]
            __snake_case            =	[self.eos_token_id, self.cur_lang_code]









"""simple docstring"""

from __future__ import annotations

_UpperCamelCase		     =    []



def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						bool:
 for i in range(len(lowercase__   )   ):
  if board[row][i] == 1:
   return False
 for i in range(len(lowercase__   )   ):
  if board[i][column] == 1:
   return False
 for i, j in zip(range(lowercase__					,					-1					,					-1   )					,					range(lowercase__					,					-1					,					-1   )   ):
  if board[i][j] == 1:
   return False
 for i, j in zip(range(lowercase__					,					-1					,					-1   )					,					range(lowercase__					,					len(lowercase__   )   )   ):
  if board[i][j] == 1:
   return False
 return True



def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__   )			->						bool:
 if row >= len(lowercase__   ):
  solution.append(lowercase__   )
  printboard(lowercase__   )
  print()
  return True
 for i in range(len(lowercase__   )   ):
  if is_safe(lowercase__					,					lowercase__					,					lowercase__   ):
   lowerCAmelCase__   :				List[Any] 			=				1
   solve(lowercase__					,					row + 1   )
   lowerCAmelCase__   :				Dict 			=				0
 return False



def       SCREAMING_SNAKE_CASE							( lowercase__   )			->						None:
 for i in range(len(lowercase__   )   ):
  for j in range(len(lowercase__   )   ):
   if board[i][j] == 1:
    print("Q"					,					end=" "   )
   else:
    print("."					,					end=" "   )
  print()


# n=int(input("The no. of queens"))
_UpperCamelCase		     =    8
_UpperCamelCase		     =    [[0 for i in range(n)] for j in range(n)]
solve(board, 0)






print("""The total no. of solutions are :""", len(solution))






