


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


_snake_case					:		Union[str, Any]      =    logging.get_logger(__name__)

_snake_case					:		List[str]      =    {
    "google/pegasus-large": "https://huggingface.co/google/pegasus-large/resolve/main/config.json",
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}

class     a		(_lowerCAmelCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							str					  =  "pegasus"
							__UpperCAmelCase   :							Tuple					  =  ["past_key_values"]
							__UpperCAmelCase   :							str					  =  {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}

							def __init__(							self	:  List[Any]   ,     lowerCamelCase	:  Optional[Any]=50265   ,     lowerCamelCase	:  Union[str, Any]=1024   ,     lowerCamelCase	:  Dict=12   ,     lowerCamelCase	:  Tuple=4096   ,     lowerCamelCase	:  str=16   ,     lowerCamelCase	:  Optional[Any]=12   ,     lowerCamelCase	:  Union[str, Any]=4096   ,     lowerCamelCase	:  Dict=16   ,     lowerCamelCase	:  Any=0.0   ,     lowerCamelCase	:  int=0.0   ,     lowerCamelCase	:  Any=True   ,     lowerCamelCase	:  Tuple=True   ,     lowerCamelCase	:  Tuple="gelu"   ,     lowerCamelCase	:  Union[str, Any]=1024   ,     lowerCamelCase	:  Tuple=0.1   ,     lowerCamelCase	:  Dict=0.0   ,     lowerCamelCase	:  Optional[int]=0.0   ,     lowerCamelCase	:  Optional[Any]=0.02   ,     lowerCamelCase	:  Tuple=0   ,     lowerCamelCase	:  List[Any]=False   ,     lowerCamelCase	:  Any=0   ,     lowerCamelCase	:  Optional[Any]=1   ,     lowerCamelCase	:  List[str]=1   ,     **lowerCamelCase	:  Union[str, Any]   ,     )     ->   List[str]:
														__snake_case		:      Optional[int]										=       vocab_size
														__snake_case		:      Tuple										=       max_position_embeddings
														__snake_case		:      Union[str, Any]										=       d_model
														__snake_case		:      Dict										=       encoder_ffn_dim
														__snake_case		:      Tuple										=       encoder_layers
														__snake_case		:      str										=       encoder_attention_heads
														__snake_case		:      Any										=       decoder_ffn_dim
														__snake_case		:      Union[str, Any]										=       decoder_layers
														__snake_case		:      int										=       decoder_attention_heads
														__snake_case		:      List[Any]										=       dropout
														__snake_case		:      Dict										=       attention_dropout
														__snake_case		:      Union[str, Any]										=       activation_dropout
														__snake_case		:      str										=       activation_function
														__snake_case		:      List[Any]										=       init_std
														__snake_case		:      Tuple										=       encoder_layerdrop
														__snake_case		:      Dict										=       decoder_layerdrop
														__snake_case		:      Any										=       use_cache
														__snake_case		:      str										=       encoder_layers
														__snake_case		:      Optional[Any]										=       scale_embedding  # scale factor will be sqrt(d_model) if True
														super().__init__(
														    pad_token_id=lowerCamelCase   ,     eos_token_id=lowerCamelCase   ,     is_encoder_decoder=lowerCamelCase   ,     decoder_start_token_id=lowerCamelCase   ,     forced_eos_token_id=lowerCamelCase   ,     **lowerCamelCase   ,     )

							@property
							def    __snake_case (							self	:  Dict    )     ->   int:
														return self.encoder_attention_heads






							@property
							def    __snake_case (							self	:  int    )     ->   int:
														return self.d_model





from __future__ import annotations

_snake_case					:		Union[str, Any]      =    []







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







def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase     ):
							if row >= len(__lowerCamelCase     ):
														solution.append(__lowerCamelCase     )
														printboard(__lowerCamelCase     )
														print()
														return True
							for i in range(len(__lowerCamelCase     )     ):
														if is_safe(__lowerCamelCase							,     __lowerCamelCase							,     __lowerCamelCase     ):
																					__snake_case		:      Optional[Any]										=       1
																					solve(__lowerCamelCase							,     row + 1     )
																					__snake_case		:      Union[str, Any]										=       0
							return False







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


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

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

