'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


SCREAMING_SNAKE_CASE :	Any							     =		logging.get_logger(__name__)

SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		{
    """facebook/deit-base-distilled-patch16-224""": (
        """https://huggingface.co/facebook/deit-base-patch16-224/resolve/main/config.json"""
    ),
    # See all DeiT models at https://huggingface.co/models?filter=deit
}
class    A_ (       UpperCamelCase_ ):
  _SCREAMING_SNAKE_CASE    				=			"""deit"""

  def __init__(		self :      Any     ,							__SCREAMING_SNAKE_CASE :      Tuple=7_68     ,							__SCREAMING_SNAKE_CASE :      Optional[Any]=12     ,							__SCREAMING_SNAKE_CASE :      str=12     ,							__SCREAMING_SNAKE_CASE :      Tuple=30_72     ,							__SCREAMING_SNAKE_CASE :      Any="gelu"     ,							__SCREAMING_SNAKE_CASE :      List[str]=0.0     ,							__SCREAMING_SNAKE_CASE :      Any=0.0     ,							__SCREAMING_SNAKE_CASE :      Union[str, Any]=0.02     ,							__SCREAMING_SNAKE_CASE :      Tuple=1E-12     ,							__SCREAMING_SNAKE_CASE :      str=2_24     ,							__SCREAMING_SNAKE_CASE :      List[Any]=16     ,							__SCREAMING_SNAKE_CASE :      str=3     ,							__SCREAMING_SNAKE_CASE :      Union[str, Any]=True     ,							__SCREAMING_SNAKE_CASE :      Tuple=16     ,							**__SCREAMING_SNAKE_CASE :      str     ,							):
   super().__init__(**__a       )

   __a       =  hidden_size
   __a       =  num_hidden_layers
   __a       =  num_attention_heads
   __a       =  intermediate_size
   __a       =  hidden_act
   __a       =  hidden_dropout_prob
   __a       =  attention_probs_dropout_prob
   __a       =  initializer_range
   __a       =  layer_norm_eps
   __a       =  image_size
   __a       =  patch_size
   __a       =  num_channels
   __a       =  qkv_bias
   __a       =  encoder_stride
class    A_ (       UpperCamelCase_ ):
  _SCREAMING_SNAKE_CASE    				=			version.parse("""1.11""" )

  @property
  def 		_UpperCAmelCase   (		self :      Any       ):
   return OrderedDict(
       [
           ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
       ]       )

  @property
  def 		_UpperCAmelCase   (		self :      str       ):
   return 1E-4



from __future__ import annotations

SCREAMING_SNAKE_CASE :	Optional[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					):
   __a       =  1
   solve(_A							,				row + 1					)
   __a       =  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"))
SCREAMING_SNAKE_CASE :	List[str]							     =		8
SCREAMING_SNAKE_CASE :	str							     =		[[0 for i in range(n)] for j in range(n)]
solve(board, 0)






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


