
'''simple docstring'''



from __future__ import annotations

_lowercase    =		[]


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


def A				(__lowerCamelCase				:list[list[int]]		):
						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"))
_lowercase    =		8
_lowercase    =		[[0 for i in range(n)] for j in range(n)]
solve(board, 0)





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






'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

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


_lowercase    =		logging.get_logger(__name__)

_lowercase    =		{
    """YituTech/conv-bert-base""": """https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json""",
    """YituTech/conv-bert-medium-small""": (
        """https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"""
    ),
    """YituTech/conv-bert-small""": """https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json""",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}




class   UpperCAmelCase_					(		_SCREAMING_SNAKE_CASE			):






						'''simple docstring'''






						_lowercase		:				List[Any]									=       '''convbert'''




						def __init__( self   ,       _lowercase=30_522   ,       _lowercase=768   ,       _lowercase=12   ,       _lowercase=12   ,       _lowercase=3_072   ,       _lowercase="gelu"   ,       _lowercase=0.1   ,       _lowercase=0.1   ,       _lowercase=512   ,       _lowercase=2   ,       _lowercase=0.02   ,       _lowercase=1e-12   ,       _lowercase=1   ,       _lowercase=0   ,       _lowercase=2   ,       _lowercase=768   ,       _lowercase=2   ,       _lowercase=9   ,       _lowercase=1   ,       _lowercase=None   ,       **_lowercase   ,       ):

												"""simple docstring"""



												super().__init__(
												    pad_token_id=_lowercase   ,       bos_token_id=_lowercase   ,       eos_token_id=_lowercase   ,       **_lowercase   ,       )

												_lowerCAmelCase  						=			vocab_size
												_lowerCAmelCase  						=			hidden_size
												_lowerCAmelCase  						=			num_hidden_layers
												_lowerCAmelCase  						=			num_attention_heads
												_lowerCAmelCase  						=			intermediate_size
												_lowerCAmelCase  						=			hidden_act
												_lowerCAmelCase  						=			hidden_dropout_prob
												_lowerCAmelCase  						=			attention_probs_dropout_prob
												_lowerCAmelCase  						=			max_position_embeddings
												_lowerCAmelCase  						=			type_vocab_size
												_lowerCAmelCase  						=			initializer_range
												_lowerCAmelCase  						=			layer_norm_eps
												_lowerCAmelCase  						=			embedding_size
												_lowerCAmelCase  						=			head_ratio
												_lowerCAmelCase  						=			conv_kernel_size
												_lowerCAmelCase  						=			num_groups
												_lowerCAmelCase  						=			classifier_dropout






class   UpperCAmelCase_					(		_SCREAMING_SNAKE_CASE			):






						'''simple docstring'''






						@property
						def  _lowercase     ( self				):

												"""simple docstring"""



												if self.task == "multiple-choice":
																		_lowerCAmelCase  						=			{0: """batch""", 1: """choice""", 2: """sequence"""}
												else:
																		_lowerCAmelCase  						=			{0: """batch""", 1: """sequence"""}
												return OrderedDict(
												    [
												        ("""input_ids""", dynamic_axis),
												        ("""attention_mask""", dynamic_axis),
												        ("""token_type_ids""", dynamic_axis),
												    ]				)
