

from __future__ import annotations

lowerCAmelCase							:  List[Any]            =						[]







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







def       A_				(   _UpperCAmelCase    ,     _UpperCAmelCase   ):
						if row >= len(_UpperCAmelCase   ):
												solution.append(_UpperCAmelCase   )
												printboard(_UpperCAmelCase   )
												print()
												return True
						for i in range(len(_UpperCAmelCase   )   ):
												if is_safe(_UpperCAmelCase    ,     _UpperCAmelCase    ,     _UpperCAmelCase   ):
																		SCREAMING_SNAKE_CASE_:			List[str]  		=	1
																		solve(_UpperCAmelCase    ,     row + 1   )
																		SCREAMING_SNAKE_CASE_:			Optional[int]  		=	0
						return False







def       A_				(   _UpperCAmelCase   ):
						for i in range(len(_UpperCAmelCase   )   ):
												for j in range(len(_UpperCAmelCase   )   ):
																		if board[i][j] == 1:
																								print("Q"    ,     end=" "   )
																		else:
																								print("."    ,     end=" "   )
												print()


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



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









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


lowerCAmelCase							:  Optional[int]            =						logging.get_logger(__name__)

lowerCAmelCase							:  int            =						{
    """google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
    """google/fnet-large""": """https://huggingface.co/google/fnet-large/resolve/main/config.json"""
    # See all FNet models at https://huggingface.co/models?filter=fnet
}



class   __lowercase    (			UpperCAmelCase_     ):




			"""simple docstring"""







			_UpperCAmelCase       :							int      							=					'''fnet'''



			def __init__(			self  :					Optional[Any]       ,						lowerCAmelCase__  :					List[str]=3_2000       ,						lowerCAmelCase__  :					Union[str, Any]=768       ,						lowerCAmelCase__  :					Optional[Any]=12       ,						lowerCAmelCase__  :					Tuple=3072       ,						lowerCAmelCase__  :					Any="gelu_new"       ,						lowerCAmelCase__  :					Union[str, Any]=0.1       ,						lowerCAmelCase__  :					Optional[Any]=512       ,						lowerCAmelCase__  :					int=4       ,						lowerCAmelCase__  :					List[Any]=0.02       ,						lowerCAmelCase__  :					Union[str, Any]=1E-12       ,						lowerCAmelCase__  :					Optional[int]=False       ,						lowerCAmelCase__  :					Any=512       ,						lowerCAmelCase__  :					Optional[int]=3       ,						lowerCAmelCase__  :					int=1       ,						lowerCAmelCase__  :					List[Any]=2       ,						**lowerCAmelCase__  :					Optional[int]       ,						):
									super().__init__(pad_token_id=lowerCAmelCase__       ,						bos_token_id=lowerCAmelCase__       ,						eos_token_id=lowerCAmelCase__       ,						**lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_:			str  		=	vocab_size
									SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	max_position_embeddings
									SCREAMING_SNAKE_CASE_:			Tuple  		=	hidden_size
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	num_hidden_layers
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	intermediate_size
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	hidden_act
									SCREAMING_SNAKE_CASE_:			Any  		=	hidden_dropout_prob
									SCREAMING_SNAKE_CASE_:			int  		=	initializer_range
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	type_vocab_size
									SCREAMING_SNAKE_CASE_:			int  		=	layer_norm_eps
									SCREAMING_SNAKE_CASE_:			Union[str, Any]  		=	use_tpu_fourier_optimizations
									SCREAMING_SNAKE_CASE_:			int  		=	tpu_short_seq_length






