





from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase       		=      logging.get_logger(__name__)

lowerCAmelCase       		=      {
    """kssteven/ibert-roberta-base""": """https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json""",
    """kssteven/ibert-roberta-large""": """https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json""",
    """kssteven/ibert-roberta-large-mnli""": (
        """https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json"""
    ),
}
class 		lowerCamelCase  (      _A       ):
	snake_case_      =   "ibert"



	def __init__(   self		,      a_=30_522		,      a_=768		,      a_=12		,      a_=12		,      a_=3_072		,      a_="gelu"		,      a_=0.1		,      a_=0.1		,      a_=512		,      a_=2		,      a_=0.02		,      a_=1e-1_2		,      a_=1		,      a_=0		,      a_=2		,      a_="absolute"		,      a_=False		,      a_="none"		,      **a_		,      ):
			super().__init__(pad_token_id=a_		,      bos_token_id=a_		,      eos_token_id=a_		,      **a_	)

			lowerCAmelCase     :    Any						=   vocab_size
			lowerCAmelCase     :    int						=   hidden_size
			lowerCAmelCase     :    Optional[Any]						=   num_hidden_layers
			lowerCAmelCase     :    str						=   num_attention_heads
			lowerCAmelCase     :    Union[str, Any]						=   hidden_act
			lowerCAmelCase     :    Optional[int]						=   intermediate_size
			lowerCAmelCase     :    Tuple						=   hidden_dropout_prob
			lowerCAmelCase     :    str						=   attention_probs_dropout_prob
			lowerCAmelCase     :    Optional[Any]						=   max_position_embeddings
			lowerCAmelCase     :    Union[str, Any]						=   type_vocab_size
			lowerCAmelCase     :    Optional[Any]						=   initializer_range
			lowerCAmelCase     :    List[Any]						=   layer_norm_eps
			lowerCAmelCase     :    List[str]						=   position_embedding_type
			lowerCAmelCase     :    Union[str, Any]						=   quant_mode
			lowerCAmelCase     :    str						=   force_dequant






class 		lowerCamelCase  (      _A       ):



	@property
	def   _lowerCamelCase    (   self	):
			if self.task == "multiple-choice":
					lowerCAmelCase     :    List[Any]						=   {0: "batch", 1: "choice", 2: "sequence"}
			else:
					lowerCAmelCase     :    Any						=   {0: "batch", 1: "sequence"}
			return OrderedDict(
			    [
			        ("input_ids", dynamic_axis),
			        ("attention_mask", dynamic_axis),
			    ]	)










'''simple docstring'''






from __future__ import annotations

lowerCAmelCase       		=      []






def      __A						(							a_						:  list[list[int]]      ,a_						:  int      ,a_						:  int	):
		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_						:  list[list[int]]      ,a_						:  int	):
		if row >= len(a_	):
				solution.append(a_	)
				printboard(a_	)
				print()
				return True
		for i in range(len(a_	)	):
				if is_safe(a_      ,a_      ,a_	):
						lowerCAmelCase     :    Any						=   1
						solve(a_      ,row + 1	)
						lowerCAmelCase     :    List[Any]						=   0
		return False






def      __A						(							a_						:  list[list[int]]	):
		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"))
lowerCAmelCase       		=      8
lowerCAmelCase       		=      [[0 for i in range(n)] for j in range(n)]
solve(board, 0)

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



