



'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

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


A					:       Union[str, Any]									=     logging.get_logger(__name__)

A					:       List[str]									=     {
    """roberta-base""": """https://huggingface.co/roberta-base/resolve/main/config.json""",
    """roberta-large""": """https://huggingface.co/roberta-large/resolve/main/config.json""",
    """roberta-large-mnli""": """https://huggingface.co/roberta-large-mnli/resolve/main/config.json""",
    """distilroberta-base""": """https://huggingface.co/distilroberta-base/resolve/main/config.json""",
    """roberta-base-openai-detector""": """https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json""",
    """roberta-large-openai-detector""": """https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json""",
}





class 				lowerCAmelCase_						(			A__		):
    __UpperCAmelCase				=			'roberta'





    def __init__(							self							:							Optional[Any],							_snake_case							:							Optional[Any]=50_265,							_snake_case							:							Optional[Any]=768,							_snake_case							:							str=12,							_snake_case							:							Tuple=12,							_snake_case							:							int=3_072,							_snake_case							:							List[Any]="gelu",							_snake_case							:							List[Any]=0.1,							_snake_case							:							str=0.1,							_snake_case							:							List[str]=512,							_snake_case							:							str=2,							_snake_case							:							Optional[Any]=0.02,							_snake_case							:							Optional[Any]=1E-12,							_snake_case							:							Optional[int]=1,							_snake_case							:							Union[str, Any]=0,							_snake_case							:							List[str]=2,							_snake_case							:							Optional[Any]="absolute",							_snake_case							:							Any=True,							_snake_case							:							Any=None,							**_snake_case							:							Dict,							):



       '''simple docstring'''







       super().__init__(pad_token_id=UpperCamelCase_,							bos_token_id=UpperCamelCase_,							eos_token_id=UpperCamelCase_,							**UpperCamelCase_      )

       snake_case       :				Optional[Any]		    =vocab_size
       snake_case       :				Dict		    =hidden_size
       snake_case       :				Optional[Any]		    =num_hidden_layers
       snake_case       :				Union[str, Any]		    =num_attention_heads
       snake_case       :				List[str]		    =hidden_act
       snake_case       :				int		    =intermediate_size
       snake_case       :				Any		    =hidden_dropout_prob
       snake_case       :				Any		    =attention_probs_dropout_prob
       snake_case       :				str		    =max_position_embeddings
       snake_case       :				str		    =type_vocab_size
       snake_case       :				Dict		    =initializer_range
       snake_case       :				str		    =layer_norm_eps
       snake_case       :				Any		    =position_embedding_type
       snake_case       :				str		    =use_cache
       snake_case       :				Tuple		    =classifier_dropout





class 				lowerCAmelCase_						(			A__		):





    @property
    def 	__snake_case  (							self							:							int      ):



       '''simple docstring'''







       if self.task == "multiple-choice":
          snake_case       :				List[Any]		    ={0: '''batch''', 1: '''choice''', 2: '''sequence'''}
       else:
          snake_case       :				Dict		    ={0: '''batch''', 1: '''sequence'''}
       return OrderedDict(
           [
               ('''input_ids''', dynamic_axis),
               ('''attention_mask''', dynamic_axis),
           ]      )









'''simple docstring'''
from __future__ import annotations

from decimal import Decimal

from numpy import array


def      a (     __a  )    ->      list[list[float]]:



					'''simple docstring'''






					UpperCamelCase__  :int				   =					Decimal

					# Check if the provided matrix has 2 rows and 2 columns
					# since this implementation only works for 2x2 matrices
					if len(__a  ) == 2 and len(matrix[0]  ) == 2 and len(matrix[1]  ) == 2:
										# Calculate the determinant of the matrix
										UpperCamelCase__  :str				   =					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
										UpperCamelCase__  :List[Any]				   =					[[0.0, 0.0], [0.0, 0.0]]
										UpperCamelCase__   ,							UpperCamelCase__  :Union[str, Any]				   =					matrix[1][1], matrix[0][0]
										UpperCamelCase__   ,							UpperCamelCase__  :Dict				   =					-matrix[1][0], -matrix[0][1]

										# Calculate the inverse of the matrix
										return [
										    [(float(d(__a  )  ) / determinant) or 0.0 for n in row] for row in swapped_matrix
										]
					elif (
					    len(__a  ) == 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
										UpperCamelCase__  :int				   =					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
										UpperCamelCase__  :List[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  )],
										]
										UpperCamelCase__  :Tuple				   =					(d(matrix[1][1]  ) * d(matrix[2][2]  )) - (
										    d(matrix[1][2]  ) * d(matrix[2][1]  )
										)
										UpperCamelCase__  :List[str]				   =					-(
										    (d(matrix[1][0]  ) * d(matrix[2][2]  )) - (d(matrix[1][2]  ) * d(matrix[2][0]  ))
										)
										UpperCamelCase__  :Union[str, Any]				   =					(d(matrix[1][0]  ) * d(matrix[2][1]  )) - (
										    d(matrix[1][1]  ) * d(matrix[2][0]  )
										)
										UpperCamelCase__  :List[Any]				   =					-(
										    (d(matrix[0][1]  ) * d(matrix[2][2]  )) - (d(matrix[0][2]  ) * d(matrix[2][1]  ))
										)
										UpperCamelCase__  :Optional[int]				   =					(d(matrix[0][0]  ) * d(matrix[2][2]  )) - (
										    d(matrix[0][2]  ) * d(matrix[2][0]  )
										)
										UpperCamelCase__  :List[Any]				   =					-(
										    (d(matrix[0][0]  ) * d(matrix[2][1]  )) - (d(matrix[0][1]  ) * d(matrix[2][0]  ))
										)
										UpperCamelCase__  :List[Any]				   =					(d(matrix[0][1]  ) * d(matrix[1][2]  )) - (
										    d(matrix[0][2]  ) * d(matrix[1][1]  )
										)
										UpperCamelCase__  :List[str]				   =					-(
										    (d(matrix[0][0]  ) * d(matrix[1][2]  )) - (d(matrix[0][2]  ) * d(matrix[1][0]  ))
										)
										UpperCamelCase__  :Dict				   =					(d(matrix[0][0]  ) * d(matrix[1][1]  )) - (
										    d(matrix[0][1]  ) * d(matrix[1][0]  )
										)

										# Transpose the cofactor matrix (Adjoint matrix)
										UpperCamelCase__  :Optional[Any]				   =					array(__a  )
										for i in range(3  ):
															for j in range(3  ):
																				UpperCamelCase__  :Optional[Any]				   =					cofactor_matrix[j][i]

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

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