import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase			:							Any     =logging.get_logger(__name__)

lowerCAmelCase			:							str     ="""▁"""

lowerCAmelCase			:							Dict     ={"""vocab_file""": """sentencepiece.bpe.model""", """monolingual_vocab_file""": """dict.txt"""}

lowerCAmelCase			:							Dict     ={
    """vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model""",
    },
    """monolingual_vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt""",
    },
}

lowerCAmelCase			:							Optional[int]     ={"""vinai/bartpho-syllable""": 1024}




class 	__snake_case	( __lowerCAmelCase		):





						'''simple docstring'''






						_snake_case    		=       VOCAB_FILES_NAMES
						_snake_case    		=       PRETRAINED_VOCAB_FILES_MAP
						_snake_case    		=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_snake_case    		=       ["input_ids", "attention_mask"]



						def __init__(					self     :				Optional[Any]    ,  _UpperCamelCase     :				Union[str, Any]    ,  _UpperCamelCase     :				Optional[int]    ,  _UpperCamelCase     :				int="<s>"    ,  _UpperCamelCase     :				Dict="</s>"    ,  _UpperCamelCase     :				Dict="</s>"    ,  _UpperCamelCase     :				str="<s>"    ,  _UpperCamelCase     :				Optional[int]="<unk>"    ,  _UpperCamelCase     :				str="<pad>"    ,  _UpperCamelCase     :				List[Any]="<mask>"    ,  _UpperCamelCase     :				Optional[Dict[str, Any]] = None    ,  **_UpperCamelCase     :				Optional[int]    ,  )				->None:


										"""simple docstring"""


										_lowerCamelCase     :		Optional[Any] 						=						AddedToken(_UpperCamelCase    ,  lstrip=_UpperCamelCase    ,  rstrip=_UpperCamelCase) if isinstance(_UpperCamelCase    ,  _UpperCamelCase) else mask_token

										_lowerCamelCase     :		List[Any] 						=						{} if sp_model_kwargs is None else sp_model_kwargs

										super().__init__(
										    bos_token=_UpperCamelCase    ,  eos_token=_UpperCamelCase    ,  unk_token=_UpperCamelCase    ,  sep_token=_UpperCamelCase    ,  cls_token=_UpperCamelCase    ,  pad_token=_UpperCamelCase    ,  mask_token=_UpperCamelCase    ,  sp_model_kwargs=self.sp_model_kwargs    ,  **_UpperCamelCase    ,  )

										_lowerCamelCase     :		Dict 						=						vocab_file
										_lowerCamelCase     :		List[str] 						=						monolingual_vocab_file
										_lowerCamelCase     :		Optional[int] 						=						spm.SentencePieceProcessor(**self.sp_model_kwargs)
										self.sp_model.Load(str(_UpperCamelCase))

										# Load the reduced vocab

										# Keep order of special tokens for backward compatibility
										_lowerCamelCase     :		Union[str, Any] 						=						{}
										_lowerCamelCase     :		Dict 						=						0
										for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
														if str(_UpperCamelCase) not in self.fairseq_tokens_to_ids:
																		_lowerCamelCase     :		Dict 						=						cnt
																		cnt += 1
										with open(_UpperCamelCase    ,  """r"""    ,  encoding="""utf-8""") as f:
														for line in f.readlines():
																		_lowerCamelCase     :		Optional[Any] 						=						line.strip().split()[0]
																		_lowerCamelCase     :		Optional[int] 						=						len(self.fairseq_tokens_to_ids)
										if str(_UpperCamelCase) not in self.fairseq_tokens_to_ids:
														_lowerCamelCase     :		Dict 						=						len(self.fairseq_tokens_to_ids)

										_lowerCamelCase     :		Any 						=						{v: k for k, v in self.fairseq_tokens_to_ids.items()}



						def __getstate__(					self     :				Union[str, Any])				->List[str]:


										"""simple docstring"""


										_lowerCamelCase     :		Tuple 						=						self.__dict__.copy()
										_lowerCamelCase     :		Optional[int] 						=						None
										_lowerCamelCase     :		Optional[Any] 						=						self.sp_model.serialized_model_proto()
										return state



						def __setstate__(					self     :				int    ,  _UpperCamelCase     :				str)				->List[Any]:


										"""simple docstring"""


										_lowerCamelCase     :		Dict 						=						d

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

										_lowerCamelCase     :		Dict 						=						spm.SentencePieceProcessor(**self.sp_model_kwargs)
										self.sp_model.LoadFromSerializedProto(self.sp_model_proto)



						def 	_SCREAMING_SNAKE_CASE    (					self     :				List[str]    ,  _UpperCamelCase     :				List[int]    ,  _UpperCamelCase     :				Optional[List[int]] = None)				->List[int]:


										"""simple docstring"""


										if token_ids_a is None:
														return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										_lowerCamelCase     :		List[str] 						=						[self.cls_token_id]
										_lowerCamelCase     :		int 						=						[self.sep_token_id]
										return cls + token_ids_a + sep + sep + token_ids_a + sep



						def 	_SCREAMING_SNAKE_CASE    (					self     :				str    ,  _UpperCamelCase     :				List[int]    ,  _UpperCamelCase     :				Optional[List[int]] = None    ,  _UpperCamelCase     :				bool = False)				->List[int]:


										"""simple docstring"""


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

										if token_ids_a is None:
														return [1] + ([0] * len(_UpperCamelCase)) + [1]
										return [1] + ([0] * len(_UpperCamelCase)) + [1, 1] + ([0] * len(_UpperCamelCase)) + [1]



						def 	_SCREAMING_SNAKE_CASE    (					self     :				Tuple    ,  _UpperCamelCase     :				List[int]    ,  _UpperCamelCase     :				Optional[List[int]] = None)				->List[int]:


										"""simple docstring"""


										_lowerCamelCase     :		Union[str, Any] 						=						[self.sep_token_id]
										_lowerCamelCase     :		str 						=						[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]



						@property
						def 	_SCREAMING_SNAKE_CASE    (					self     :				Any)				->Optional[int]:


										"""simple docstring"""


										return len(self.fairseq_ids_to_tokens)



						def 	_SCREAMING_SNAKE_CASE    (					self     :				Dict)				->int:


										"""simple docstring"""


										_lowerCamelCase     :		Any 						=						{self.convert_ids_to_tokens(_UpperCamelCase): i for i in range(self.vocab_size)}
										vocab.update(self.added_tokens_encoder)
										return vocab



						def 	_SCREAMING_SNAKE_CASE    (					self     :				Any    ,  _UpperCamelCase     :				str)				->List[str]:


										"""simple docstring"""


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



						def 	_SCREAMING_SNAKE_CASE    (					self     :				Union[str, Any]    ,  _UpperCamelCase     :				Union[str, Any])				->List[Any]:


										"""simple docstring"""


										if token in self.fairseq_tokens_to_ids:
														return self.fairseq_tokens_to_ids[token]
										else:
														return self.unk_token_id



						def 	_SCREAMING_SNAKE_CASE    (					self     :				Tuple    ,  _UpperCamelCase     :				List[str])				->Union[str, Any]:


										"""simple docstring"""


										return self.fairseq_ids_to_tokens[index]



						def 	_SCREAMING_SNAKE_CASE    (					self     :				List[Any]    ,  _UpperCamelCase     :				Optional[Any])				->Optional[Any]:


										"""simple docstring"""


										_lowerCamelCase     :		Optional[Any] 						=						"""""".join(_UpperCamelCase).replace(_UpperCamelCase    ,  """ """).strip()
										return out_string




						def 	_SCREAMING_SNAKE_CASE    (					self     :				List[Any]    ,  _UpperCamelCase     :				str    ,  _UpperCamelCase     :				Optional[str] = None)				->Tuple[str]:


										"""simple docstring"""


										if not os.path.isdir(_UpperCamelCase):
														logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
														return
										_lowerCamelCase     :		List[str] 						=						os.path.join(
										    _UpperCamelCase    ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""])
										_lowerCamelCase     :		List[Any] 						=						os.path.join(
										    _UpperCamelCase    ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""monolingual_vocab_file"""]    ,  )

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

										if os.path.abspath(self.monolingual_vocab_file) != os.path.abspath(
										    _UpperCamelCase) and os.path.isfile(self.monolingual_vocab_file):
														copyfile(self.monolingual_vocab_file    ,  _UpperCamelCase)
										elif not os.path.isfile(self.monolingual_vocab_file):
														with open(_UpperCamelCase    ,  """w"""    ,  encoding="""utf-8""") as fp:
																		for token in self.fairseq_tokens_to_ids:
																						if token not in self.all_special_tokens:
																										fp.write(F"""{str(_UpperCamelCase)} \n""")

										return out_vocab_file, out_monolingual_vocab_file





from __future__ import annotations

lowerCAmelCase			:							int     =[]







def 						A__  (					__A   , __A   , __A	):







    '''simple docstring'''
    for i in range(len(__A	)	):
        if board[row][i] == 1:
            return False
    for i in range(len(__A	)	):
        if board[i][column] == 1:
            return False
    for i, j in zip(range(__A   , -1   , -1	)   , range(__A   , -1   , -1	)	):
        if board[i][j] == 1:
            return False
    for i, j in zip(range(__A   , -1   , -1	)   , range(__A   , len(__A	)	)	):
        if board[i][j] == 1:
            return False
    return True







def 						A__  (					__A   , __A	):







    '''simple docstring'''
    if row >= len(__A	):
        solution.append(__A	)
        printboard(__A	)
        print()
        return True
    for i in range(len(__A	)	):
        if is_safe(__A   , __A   , __A	):
            _lowerCamelCase     :		int 						=						1
            solve(__A   , row + 1	)
            _lowerCamelCase     :		List[str] 						=						0
    return False







def 						A__  (					__A	):







    '''simple docstring'''
    for i in range(len(__A	)	):
        for j in range(len(__A	)	):
            if board[i][j] == 1:
                print("""Q"""   , end=""" """	)
            else:
                print("""."""   , end=""" """	)
        print()


# n=int(input("The no. of queens"))
lowerCAmelCase			:							int     =8
lowerCAmelCase			:							Union[str, Any]     =[[0 for i in range(n)] for j in range(n)]
solve(board, 0)
print("The total no. of solutions are :", len(solution))




