





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


lowerCAmelCase       		=      logging.get_logger(__name__)

lowerCAmelCase       		=      {
    """facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/config.json""",
    # See all XGLM models at https://huggingface.co/models?filter=xglm
}
class 		lowerCamelCase  (      _A       ):
	snake_case_      =   "xglm"
	snake_case_      =   ["past_key_values"]

	snake_case_      =   {
	    "num_attention_heads": "attention_heads",
	    "hidden_size": "d_model",
	    "num_hidden_layers": "num_layers",
	}



	def __init__(   self		,      a_=256_008		,      a_=2_048		,      a_=1_024		,      a_=4_096		,      a_=24		,      a_=16		,      a_="gelu"		,      a_=0.1		,      a_=0.1		,      a_=0.0		,      a_=0.0		,      a_=0.02		,      a_=True		,      a_=True		,      a_=2		,      a_=1		,      a_=0		,      a_=2		,      **a_		,      ):
			lowerCAmelCase     :    List[Any]						=   vocab_size
			lowerCAmelCase     :    Optional[int]						=   max_position_embeddings
			lowerCAmelCase     :    Union[str, Any]						=   d_model
			lowerCAmelCase     :    int						=   ffn_dim
			lowerCAmelCase     :    Tuple						=   num_layers
			lowerCAmelCase     :    Optional[int]						=   attention_heads
			lowerCAmelCase     :    int						=   activation_function
			lowerCAmelCase     :    Dict						=   dropout
			lowerCAmelCase     :    Optional[int]						=   attention_dropout
			lowerCAmelCase     :    Optional[int]						=   activation_dropout
			lowerCAmelCase     :    Tuple						=   layerdrop
			lowerCAmelCase     :    Dict						=   init_std
			lowerCAmelCase     :    Optional[int]						=   scale_embedding  # scale factor will be sqrt(d_model) if True
			lowerCAmelCase     :    Any						=   use_cache

			super().__init__(
			    pad_token_id=a_		,      bos_token_id=a_		,      eos_token_id=a_		,      decoder_start_token_id=a_		,      **a_		,      )










'''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))



