



from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType







class 	_snake_case							(			lowercase_      ):






   '''simple docstring'''






   A__	:      List[str]    =		["image_processor", "tokenizer"]
   A__	:      Tuple    =		"BlipImageProcessor"
   A__	:      List[Any]    =		("BertTokenizer", "BertTokenizerFast")


   def __init__(  self:			List[Any]   ,lowerCamelCase_:			Union[str, Any]   ,lowerCamelCase_:			List[str]				)     ->	Dict:
       UpperCAmelCase_			:    Optional[Any]   						= False
       super().__init__(__UpperCamelCase   ,__UpperCamelCase				)
       UpperCAmelCase_			:    Tuple   						= self.image_processor


   def __call__(  self:			Union[str, Any]   ,lowerCamelCase_:			Optional[int] = None   ,lowerCamelCase_:			str = None   ,lowerCamelCase_:			List[str] = True   ,lowerCamelCase_:			Union[str, Any] = False   ,lowerCamelCase_:			Optional[Any] = None   ,lowerCamelCase_:			List[str] = None   ,lowerCamelCase_:			List[str] = 0   ,lowerCamelCase_:			Optional[int] = None   ,lowerCamelCase_:			int = None   ,lowerCamelCase_:			Optional[Any] = False   ,lowerCamelCase_:			List[Any] = False   ,lowerCamelCase_:			Optional[Any] = False   ,lowerCamelCase_:			Union[str, Any] = False   ,lowerCamelCase_:			Dict = False   ,lowerCamelCase_:			Union[str, Any] = True   ,lowerCamelCase_:			Optional[Any] = None   ,**lowerCamelCase_:			str   ,)     ->	BatchEncoding:


       if images is None and text is None:
           raise ValueError("""You have to specify either images or text."""				)

       # Get only text
       if images is None:
           UpperCAmelCase_			:    str   						= self.tokenizer
           UpperCAmelCase_			:    List[str]   						= self.tokenizer(
               text=__UpperCamelCase   ,add_special_tokens=__UpperCamelCase   ,padding=__UpperCamelCase   ,truncation=__UpperCamelCase   ,max_length=__UpperCamelCase   ,stride=__UpperCamelCase   ,pad_to_multiple_of=__UpperCamelCase   ,return_attention_mask=__UpperCamelCase   ,return_overflowing_tokens=__UpperCamelCase   ,return_special_tokens_mask=__UpperCamelCase   ,return_offsets_mapping=__UpperCamelCase   ,return_token_type_ids=__UpperCamelCase   ,return_length=__UpperCamelCase   ,verbose=__UpperCamelCase   ,return_tensors=__UpperCamelCase   ,**__UpperCamelCase   ,)
           return text_encoding

       # add pixel_values
       UpperCAmelCase_			:    Union[str, Any]   						= self.image_processor(__UpperCamelCase   ,return_tensors=__UpperCamelCase				)

       if text is not None:
           UpperCAmelCase_			:    Tuple   						= self.tokenizer(
               text=__UpperCamelCase   ,add_special_tokens=__UpperCamelCase   ,padding=__UpperCamelCase   ,truncation=__UpperCamelCase   ,max_length=__UpperCamelCase   ,stride=__UpperCamelCase   ,pad_to_multiple_of=__UpperCamelCase   ,return_attention_mask=__UpperCamelCase   ,return_overflowing_tokens=__UpperCamelCase   ,return_special_tokens_mask=__UpperCamelCase   ,return_offsets_mapping=__UpperCamelCase   ,return_token_type_ids=__UpperCamelCase   ,return_length=__UpperCamelCase   ,verbose=__UpperCamelCase   ,return_tensors=__UpperCamelCase   ,**__UpperCamelCase   ,)
       else:
           UpperCAmelCase_			:    Any   						= None

       if text_encoding is not None:
           encoding_image_processor.update(__UpperCamelCase				)

       return encoding_image_processor


   def 	A__  (  self:			int   ,*lowerCamelCase_:			Union[str, Any]   ,**lowerCamelCase_:			Optional[Any]				)     ->	str:
       return self.tokenizer.batch_decode(*__UpperCamelCase   ,**__UpperCamelCase				)


   def 	A__  (  self:			Optional[Any]   ,*lowerCamelCase_:			List[str]   ,**lowerCamelCase_:			Optional[int]				)     ->	str:
       return self.tokenizer.decode(*__UpperCamelCase   ,**__UpperCamelCase				)






   @property
   def 	A__  (  self:			Union[str, Any]				)     ->	Optional[int]:
       UpperCAmelCase_			:    str   						= self.tokenizer.model_input_names
       UpperCAmelCase_			:    Optional[Any]   						= self.image_processor.model_input_names
       return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names				)				)

"""simple docstring"""







from __future__ import annotations

__SCREAMING_SNAKE_CASE    	=[]



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



def 			lowercase__(       __SCREAMING_SNAKE_CASE							:     list[list[int]]     ,			__SCREAMING_SNAKE_CASE							:     int      ):
     if row >= len(__SCREAMING_SNAKE_CASE      ):
          solution.append(__SCREAMING_SNAKE_CASE      )
          printboard(__SCREAMING_SNAKE_CASE      )
          print()
          return True
     for i in range(len(__SCREAMING_SNAKE_CASE      )      ):
          if is_safe(__SCREAMING_SNAKE_CASE     ,			__SCREAMING_SNAKE_CASE     ,			__SCREAMING_SNAKE_CASE      ):
               lowercase_	:				int													=	1
               solve(__SCREAMING_SNAKE_CASE     ,			row + 1      )
               lowercase_	:				Dict													=	0
     return False



def 			lowercase__(       __SCREAMING_SNAKE_CASE							:     list[list[int]]      ):
     for i in range(len(__SCREAMING_SNAKE_CASE      )      ):
          for j in range(len(__SCREAMING_SNAKE_CASE      )      ):
               if board[i][j] == 1:
                    print('Q'     ,			end=' '      )
               else:
                    print('.'     ,			end=' '      )
          print()


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







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

