



"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

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


__lowerCAmelCase							:       List[Any]          =       logging.get_logger(__name__)

__lowerCAmelCase							:       Dict          =       {
    '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json''',
    '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json''',
    '''junnyu/roformer_chinese_char_small''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json'''
    ),
    '''junnyu/roformer_chinese_char_base''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_discriminator''': (
        '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_generator''': (
        '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json'''
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}



class  _lowerCAmelCase     (					SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase      	=							'''roformer'''





		def __init__(       self				,     _lowercase=5_0_0_0_0				,     _lowercase=None				,     _lowercase=7_6_8				,     _lowercase=1_2				,     _lowercase=1_2				,     _lowercase=3_0_7_2				,     _lowercase="gelu"				,     _lowercase=0.1				,     _lowercase=0.1				,     _lowercase=1_5_3_6				,     _lowercase=2				,     _lowercase=0.02				,     _lowercase=1E-12				,     _lowercase=0				,     _lowercase=False				,     _lowercase=True				,     **_lowercase				,     )			->    int:







								'''simple docstring'''

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

								snake_case_ :			str            =      vocab_size
								snake_case_ :			Any            =      hidden_size if embedding_size is None else embedding_size
								snake_case_ :			List[str]            =      hidden_size
								snake_case_ :			str            =      num_hidden_layers
								snake_case_ :			Union[str, Any]            =      num_attention_heads
								snake_case_ :			Union[str, Any]            =      hidden_act
								snake_case_ :			Optional[Any]            =      intermediate_size
								snake_case_ :			List[str]            =      hidden_dropout_prob
								snake_case_ :			str            =      attention_probs_dropout_prob
								snake_case_ :			Union[str, Any]            =      max_position_embeddings
								snake_case_ :			List[str]            =      type_vocab_size
								snake_case_ :			Tuple            =      initializer_range
								snake_case_ :			str            =      layer_norm_eps
								snake_case_ :			List[str]            =      rotary_value
								snake_case_ :			str            =      use_cache




class  _lowerCAmelCase     (					SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		@property
		def  UpperCAmelCase__				(       self )			->    Mapping[str, Mapping[int, str]]:







								'''simple docstring'''

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







from __future__ import annotations

from decimal import Decimal

from numpy import array

def lowercase    (  SCREAMING_SNAKE_CASE )			->							list[list[float]]:


			'''simple docstring'''







			SCREAMING_SNAKE_CASE_								=						Decimal

			# Check if the provided matrix has 2 rows and 2 columns
			# since this implementation only works for 2x2 matrices
			if len(SCREAMING_SNAKE_CASE ) == 2 and len(matrix[0] ) == 2 and len(matrix[1] ) == 2:
						# Calculate the determinant of the matrix
						SCREAMING_SNAKE_CASE_								=						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
						SCREAMING_SNAKE_CASE_								=						[[0.0, 0.0], [0.0, 0.0]]
						SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_								=						matrix[1][1], matrix[0][0]
						SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_								=						-matrix[1][0], -matrix[0][1]

						# Calculate the inverse of the matrix
						return [
						    [(float(d(SCREAMING_SNAKE_CASE ) ) / determinant) or 0.0 for n in row] for row in swapped_matrix
						]
			elif (
			    len(SCREAMING_SNAKE_CASE ) == 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
						SCREAMING_SNAKE_CASE_								=						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
						SCREAMING_SNAKE_CASE_								=						[
						    [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 )],
						]
						SCREAMING_SNAKE_CASE_								=						(d(matrix[1][1] ) * d(matrix[2][2] )) - (
						    d(matrix[1][2] ) * d(matrix[2][1] )
						)
						SCREAMING_SNAKE_CASE_								=						-(
						    (d(matrix[1][0] ) * d(matrix[2][2] )) - (d(matrix[1][2] ) * d(matrix[2][0] ))
						)
						SCREAMING_SNAKE_CASE_								=						(d(matrix[1][0] ) * d(matrix[2][1] )) - (
						    d(matrix[1][1] ) * d(matrix[2][0] )
						)
						SCREAMING_SNAKE_CASE_								=						-(
						    (d(matrix[0][1] ) * d(matrix[2][2] )) - (d(matrix[0][2] ) * d(matrix[2][1] ))
						)
						SCREAMING_SNAKE_CASE_								=						(d(matrix[0][0] ) * d(matrix[2][2] )) - (
						    d(matrix[0][2] ) * d(matrix[2][0] )
						)
						SCREAMING_SNAKE_CASE_								=						-(
						    (d(matrix[0][0] ) * d(matrix[2][1] )) - (d(matrix[0][1] ) * d(matrix[2][0] ))
						)
						SCREAMING_SNAKE_CASE_								=						(d(matrix[0][1] ) * d(matrix[1][2] )) - (
						    d(matrix[0][2] ) * d(matrix[1][1] )
						)
						SCREAMING_SNAKE_CASE_								=						-(
						    (d(matrix[0][0] ) * d(matrix[1][2] )) - (d(matrix[0][2] ) * d(matrix[1][0] ))
						)
						SCREAMING_SNAKE_CASE_								=						(d(matrix[0][0] ) * d(matrix[1][1] )) - (
						    d(matrix[0][1] ) * d(matrix[1][0] )
						)

						# Transpose the cofactor matrix (Adjoint matrix)
						SCREAMING_SNAKE_CASE_								=						array(SCREAMING_SNAKE_CASE )
						for i in range(3 ):
									for j in range(3 ):
												SCREAMING_SNAKE_CASE_								=						cofactor_matrix[j][i]

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

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