
from __future__ import annotations






def   lowerCamelCase__							(					a		,		a		,		a		,		a		,		a		,		)      ->   None:
   _A:  Optional[Any]					=       len(a      )

   # If row is equal to the size of the board it means there are a queen in each row in
   # the current board (possible_board)
   if row == n:
      # We convert the variable possible_board that looks like this: [1, 3, 0, 2] to
      # this: ['. Q . . ', '. . . Q ', 'Q . . . ', '. . Q . ']
      boards.append(['''. ''' * i + '''Q ''' + '''. ''' * (n - 1 - i) for i in possible_board]      )
      return

   # We iterate each column in the row to find all possible results in each row
   for col in range(a      ):
      # We apply that we learned previously. First we check that in the current board
      # (possible_board) there are not other same value because if there is it means
      # that there are a collision in vertical. Then we apply the two formulas we
      # learned before:
      #
      # 45º: y - x = b or 45: row - col = b
      # 135º: y + x = b or row + col = b.
      #
      # And we verify if the results of this two formulas not exist in their variables
      # respectively.  (diagonal_right_collisions, diagonal_left_collisions)
      #
      # If any or these are True it means there is a collision so we continue to the
      # next value in the for loop.
      if (
          col in possible_board
          or row - col in diagonal_right_collisions
          or row + col in diagonal_left_collisions
      ):
         continue

      # If it is False we call dfs function again and we update the inputs
      depth_first_search(
          [*possible_board, col]		,		[*diagonal_right_collisions, row - col]		,		[*diagonal_left_collisions, row + col]		,		a		,		a		,		)






def   lowerCamelCase__							(					a      )      ->   None:
   _A:  list[list[str]]					=       []
   depth_first_search([]		,		[]		,		[]		,		a		,		a      )

   # Print all the boards
   for board in boards:
      for column in board:
         print(a      )
      print(''''''      )

   print(len(a      )		,		'''solutions were found.'''      )


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   n_queens_solution(4)





from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase__		:     Dict     			=      logging.get_logger(__name__)

UpperCAmelCase__		:     Union[str, Any]     			=      {
    'caidas/swin2sr-classicalsr-x2-64': (
        'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
    ),
}






class UpperCAmelCase   (						SCREAMING_SNAKE_CASE__   ):





   '''simple docstring'''
   __UpperCamelCase		:    Dict 				=    '''swin2sr'''

   __UpperCamelCase		:    str 				=    {
       '''hidden_size''': '''embed_dim''',
       '''num_attention_heads''': '''num_heads''',
       '''num_hidden_layers''': '''num_layers''',
   }


   def __init__(					self     :							List[str]			,			lowerCAmelCase_     :							int=6_4			,			lowerCAmelCase_     :							Optional[Any]=1			,			lowerCAmelCase_     :							Dict=3			,			lowerCAmelCase_     :							Dict=1_8_0			,			lowerCAmelCase_     :							Union[str, Any]=[6, 6, 6, 6, 6, 6]			,			lowerCAmelCase_     :							Tuple=[6, 6, 6, 6, 6, 6]			,			lowerCAmelCase_     :							int=8			,			lowerCAmelCase_     :							Any=2.0			,			lowerCAmelCase_     :							Union[str, Any]=True			,			lowerCAmelCase_     :							Dict=0.0			,			lowerCAmelCase_     :							Optional[int]=0.0			,			lowerCAmelCase_     :							int=0.1			,			lowerCAmelCase_     :							Any="gelu"			,			lowerCAmelCase_     :							List[str]=False			,			lowerCAmelCase_     :							str=0.02			,			lowerCAmelCase_     :							Optional[Any]=1e-5			,			lowerCAmelCase_     :							int=2			,			lowerCAmelCase_     :							int=1.0			,			lowerCAmelCase_     :							Any="1conv"			,			lowerCAmelCase_     :							List[str]="pixelshuffle"			,			**lowerCAmelCase_     :							str			,			):

      """simple docstring"""
      super().__init__(**lowerCAmelCase_     )

      _A:  List[str]					=       image_size
      _A:  Any					=       patch_size
      _A:  Any					=       num_channels
      _A:  Union[str, Any]					=       embed_dim
      _A:  int					=       depths
      _A:  List[Any]					=       len(lowerCAmelCase_     )
      _A:  int					=       num_heads
      _A:  Any					=       window_size
      _A:  Optional[int]					=       mlp_ratio
      _A:  int					=       qkv_bias
      _A:  List[Any]					=       hidden_dropout_prob
      _A:  List[str]					=       attention_probs_dropout_prob
      _A:  List[Any]					=       drop_path_rate
      _A:  Any					=       hidden_act
      _A:  List[str]					=       use_absolute_embeddings
      _A:  Tuple					=       layer_norm_eps
      _A:  str					=       initializer_range
      _A:  int					=       upscale
      _A:  int					=       img_range
      _A:  Optional[Any]					=       resi_connection
      _A:  int					=       upsampler



