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


snake_case :		Any							      =  logging.get_logger(__name__)

snake_case :		Optional[Any]							      =  {
    "studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
    "studio-ousia/luke-large": "https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json",
}





class       _snake_case					(     snake_case				):
			UpperCamelCase__          =    'luke'







			def __init__(				self						,   _a=50_267						,   _a=500_000						,   _a=768						,   _a=256						,   _a=12						,   _a=12						,   _a=3_072						,   _a="gelu"						,   _a=0.1						,   _a=0.1						,   _a=512						,   _a=2						,   _a=0.02						,   _a=1e-12						,   _a=True						,   _a=None						,   _a=1						,   _a=0						,   _a=2						,   **_a						,   ):
				super().__init__(pad_token_id=_a						,   bos_token_id=_a						,   eos_token_id=_a						,   **_a		)

				__magic_name__		:		Optional[Any]	   =     vocab_size
				__magic_name__		:		Optional[Any]	   =     entity_vocab_size
				__magic_name__		:		Union[str, Any]	   =     hidden_size
				__magic_name__		:		Any	   =     entity_emb_size
				__magic_name__		:		Any	   =     num_hidden_layers
				__magic_name__		:		Optional[int]	   =     num_attention_heads
				__magic_name__		:		Optional[Any]	   =     hidden_act
				__magic_name__		:		Union[str, Any]	   =     intermediate_size
				__magic_name__		:		Dict	   =     hidden_dropout_prob
				__magic_name__		:		str	   =     attention_probs_dropout_prob
				__magic_name__		:		Dict	   =     max_position_embeddings
				__magic_name__		:		int	   =     type_vocab_size
				__magic_name__		:		Tuple	   =     initializer_range
				__magic_name__		:		Any	   =     layer_norm_eps
				__magic_name__		:		List[str]	   =     use_entity_aware_attention
				__magic_name__		:		int	   =     classifier_dropout


def   lowerCAmelCase_						(					_snake_case      :  list[list[int | float]]   )				->		int:







	'''simple docstring'''


	__magic_name__		:		Any	   =     len(_snake_case   )
	__magic_name__		:		Optional[Any]	   =     len(matrix[0]   )
	__magic_name__		:		Union[str, Any]	   =     min(_snake_case      ,   _snake_case   )

	for row in range(_snake_case   ):
		# Check if diagonal element is not zero
		if matrix[row][row] != 0:
			# Eliminate all the elements below the diagonal
			for col in range(row + 1      ,   _snake_case   ):
				__magic_name__		:		Optional[Any]	   =     matrix[col][row] / matrix[row][row]
				for i in range(_snake_case      ,   _snake_case   ):
					matrix[col][i] -= multiplier * matrix[row][i]
		else:
			# Find a non-zero diagonal element to swap rows
			__magic_name__		:		str	   =     True
			for i in range(row + 1      ,   _snake_case   ):
				if matrix[i][row] != 0:
					__magic_name__   ,    __magic_name__		:		List[str]	   =     matrix[i], matrix[row]
					__magic_name__		:		Union[str, Any]	   =     False
					break
			if reduce:
				rank -= 1
				for i in range(_snake_case   ):
					__magic_name__		:		Any	   =     matrix[i][rank]

            # Reduce the row pointer by one to stay on the same row
			row -= 1

	return rank


if __name__ == "__main__":
				import doctest

				doctest.testmod()
