




from __future__ import annotations

from decimal import Decimal

from numpy import array




def 							_UpperCAmelCase  (UpperCamelCase_ : list[list[float]]       ):
				'''simple docstring'''
				_lowerCAmelCase    :    int										=      Decimal

				# Check if the provided matrix has 2 rows and 2 columns
				# since this implementation only works for 2x2 matrices
				if len(UpperCamelCase_       ) == 2 and len(matrix[0]       ) == 2 and len(matrix[1]       ) == 2:
								# Calculate the determinant of the matrix
								_lowerCAmelCase    :    Optional[Any]										=      float(
								    d(matrix[0][0]       ) * d(matrix[1][1]       ) - d(matrix[1][0]       ) * d(matrix[0][1]       )       )
								if determinant == 0:
												raise ValueError("""This matrix has no inverse."""       )

								# Creates a copy of the matrix with swapped positions of the elements
								_lowerCAmelCase    :    Union[str, Any]										=      [[0.0, 0.0], [0.0, 0.0]]
								_lowerCAmelCase					,    _lowerCAmelCase    :    Any										=      matrix[1][1], matrix[0][0]
								_lowerCAmelCase					,    _lowerCAmelCase    :    Optional[Any]										=      -matrix[1][0], -matrix[0][1]

								# Calculate the inverse of the matrix
								return [
								    [(float(d(UpperCamelCase_       )       ) / determinant) or 0.0 for n in row] for row in swapped_matrix
								]
				elif (
				    len(UpperCamelCase_       ) == 3
				    and len(matrix[0]       ) == 3
				    and len(matrix[1]       ) == 3
				    and len(matrix[2]       ) == 3
				):
								# Calculate the determinant of the matrix using Sarrus rule
								_lowerCAmelCase    :    List[str]										=      float(
								    (
								        (d(matrix[0][0]       ) * d(matrix[1][1]       ) * d(matrix[2][2]       ))
								        + (d(matrix[0][1]       ) * d(matrix[1][2]       ) * d(matrix[2][0]       ))
								        + (d(matrix[0][2]       ) * d(matrix[1][0]       ) * d(matrix[2][1]       ))
								    )
								    - (
								        (d(matrix[0][2]       ) * d(matrix[1][1]       ) * d(matrix[2][0]       ))
								        + (d(matrix[0][1]       ) * d(matrix[1][0]       ) * d(matrix[2][2]       ))
								        + (d(matrix[0][0]       ) * d(matrix[1][2]       ) * d(matrix[2][1]       ))
								    )       )
								if determinant == 0:
												raise ValueError("""This matrix has no inverse."""       )

								# Creating cofactor matrix
								_lowerCAmelCase    :    Optional[Any]										=      [
								    [d(0.0       ), d(0.0       ), d(0.0       )],
								    [d(0.0       ), d(0.0       ), d(0.0       )],
								    [d(0.0       ), d(0.0       ), d(0.0       )],
								]
								_lowerCAmelCase    :    Optional[Any]										=      (d(matrix[1][1]       ) * d(matrix[2][2]       )) - (
								    d(matrix[1][2]       ) * d(matrix[2][1]       )
								)
								_lowerCAmelCase    :    str										=      -(
								    (d(matrix[1][0]       ) * d(matrix[2][2]       )) - (d(matrix[1][2]       ) * d(matrix[2][0]       ))
								)
								_lowerCAmelCase    :    Any										=      (d(matrix[1][0]       ) * d(matrix[2][1]       )) - (
								    d(matrix[1][1]       ) * d(matrix[2][0]       )
								)
								_lowerCAmelCase    :    List[str]										=      -(
								    (d(matrix[0][1]       ) * d(matrix[2][2]       )) - (d(matrix[0][2]       ) * d(matrix[2][1]       ))
								)
								_lowerCAmelCase    :    Tuple										=      (d(matrix[0][0]       ) * d(matrix[2][2]       )) - (
								    d(matrix[0][2]       ) * d(matrix[2][0]       )
								)
								_lowerCAmelCase    :    Any										=      -(
								    (d(matrix[0][0]       ) * d(matrix[2][1]       )) - (d(matrix[0][1]       ) * d(matrix[2][0]       ))
								)
								_lowerCAmelCase    :    int										=      (d(matrix[0][1]       ) * d(matrix[1][2]       )) - (
								    d(matrix[0][2]       ) * d(matrix[1][1]       )
								)
								_lowerCAmelCase    :    Optional[Any]										=      -(
								    (d(matrix[0][0]       ) * d(matrix[1][2]       )) - (d(matrix[0][2]       ) * d(matrix[1][0]       ))
								)
								_lowerCAmelCase    :    Tuple										=      (d(matrix[0][0]       ) * d(matrix[1][1]       )) - (
								    d(matrix[0][1]       ) * d(matrix[1][0]       )
								)

								# Transpose the cofactor matrix (Adjoint matrix)
								_lowerCAmelCase    :    List[str]										=      array(UpperCamelCase_       )
								for i in range(3       ):
												for j in range(3       ):
																_lowerCAmelCase    :    List[Any]										=      cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
								_lowerCAmelCase    :    Tuple										=      array(UpperCamelCase_       )
								for i in range(3       ):
												for j in range(3       ):
																inverse_matrix[i][j] /= d(UpperCamelCase_       )

        # Calculate the inverse of the matrix
								return [[float(d(UpperCamelCase_       )       ) or 0.0 for n in row] for row in inverse_matrix]
				raise ValueError("""Please provide a matrix of size 2x2 or 3x3."""       )







import logging

from transformers.configuration_utils import PretrainedConfig


_lowerCamelCase      :  Union[str, Any]      						=						logging.getLogger(__name__)
class        __snake_case  (_a		):
				lowerCAmelCase__				=     "masked_bert"



				def __init__(      self      :		Union[str, Any]		,	_UpperCAmelCase      :		Union[str, Any]=3_0522		,	_UpperCAmelCase      :		Optional[Any]=768		,	_UpperCAmelCase      :		List[Any]=12		,	_UpperCAmelCase      :		Dict=12		,	_UpperCAmelCase      :		List[str]=3072		,	_UpperCAmelCase      :		List[Any]="gelu"		,	_UpperCAmelCase      :		Optional[Any]=0.1		,	_UpperCAmelCase      :		Optional[Any]=0.1		,	_UpperCAmelCase      :		List[Any]=512		,	_UpperCAmelCase      :		int=2		,	_UpperCAmelCase      :		Optional[int]=0.02		,	_UpperCAmelCase      :		str=1E-12		,	_UpperCAmelCase      :		Tuple=0		,	_UpperCAmelCase      :		Dict="topK"		,	_UpperCAmelCase      :		List[str]="constant"		,	_UpperCAmelCase      :		Optional[Any]=0.0		,	**_UpperCAmelCase      :		str		,	)  ->    Tuple:





								'''simple docstring'''




								super().__init__(pad_token_id=_UpperCAmelCase		,	**_UpperCAmelCase      )

								_lowerCAmelCase    :    str										=      vocab_size
								_lowerCAmelCase    :    List[str]										=      hidden_size
								_lowerCAmelCase    :    Any										=      num_hidden_layers
								_lowerCAmelCase    :    Optional[Any]										=      num_attention_heads
								_lowerCAmelCase    :    Optional[Any]										=      hidden_act
								_lowerCAmelCase    :    Union[str, Any]										=      intermediate_size
								_lowerCAmelCase    :    Tuple										=      hidden_dropout_prob
								_lowerCAmelCase    :    Optional[int]										=      attention_probs_dropout_prob
								_lowerCAmelCase    :    str										=      max_position_embeddings
								_lowerCAmelCase    :    int										=      type_vocab_size
								_lowerCAmelCase    :    List[str]										=      initializer_range
								_lowerCAmelCase    :    Optional[Any]										=      layer_norm_eps
								_lowerCAmelCase    :    Tuple										=      pruning_method
								_lowerCAmelCase    :    str										=      mask_init
								_lowerCAmelCase    :    List[str]										=      mask_scale

