


from __future__ import annotations

import math

def 			_a  (				SCREAMING_SNAKE_CASE	:				list    , SCREAMING_SNAKE_CASE	:				list     ):







 """simple docstring"""



 if len(SCREAMING_SNAKE_CASE     ) != 2 or len(a[0]     ) != 2 or len(SCREAMING_SNAKE_CASE     ) != 2 or len(b[0]     ) != 2:
  raise Exception('''Matrices are not 2x2'''     )
 UpperCamelCase__					:    Optional[int]          =   [
     [a[0][0] * b[0][0] + a[0][1] * b[1][0], a[0][0] * b[0][1] + a[0][1] * b[1][1]],
     [a[1][0] * b[0][0] + a[1][1] * b[1][0], a[1][0] * b[0][1] + a[1][1] * b[1][1]],
 ]
 return new_matrix

def 			_a  (				SCREAMING_SNAKE_CASE	:				list    , SCREAMING_SNAKE_CASE	:				list     ):







 """simple docstring"""



 return [
     [matrix_a[row][col] + matrix_b[row][col] for col in range(len(matrix_a[row]     )     )]
     for row in range(len(SCREAMING_SNAKE_CASE     )     )
 ]

def 			_a  (				SCREAMING_SNAKE_CASE	:				list    , SCREAMING_SNAKE_CASE	:				list     ):







 """simple docstring"""



 return [
     [matrix_a[row][col] - matrix_b[row][col] for col in range(len(matrix_a[row]     )     )]
     for row in range(len(SCREAMING_SNAKE_CASE     )     )
 ]

def 			_a  (				SCREAMING_SNAKE_CASE	:				list     ):







 """simple docstring"""



 if len(SCREAMING_SNAKE_CASE     ) % 2 != 0 or len(a[0]     ) % 2 != 0:
  raise Exception('''Odd matrices are not supported!'''     )

 UpperCamelCase__					:    str          =   len(SCREAMING_SNAKE_CASE     )
 UpperCamelCase__					:    Optional[Any]          =   matrix_length // 2

 UpperCamelCase__					:    List[str]          =   [[a[i][j] for j in range(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )] for i in range(SCREAMING_SNAKE_CASE     )]
 UpperCamelCase__					:    Dict          =   [
     [a[i][j] for j in range(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )] for i in range(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )
 ]

 UpperCamelCase__					:    Optional[Any]          =   [[a[i][j] for j in range(SCREAMING_SNAKE_CASE     )] for i in range(SCREAMING_SNAKE_CASE     )]
 UpperCamelCase__					:    Dict          =   [[a[i][j] for j in range(SCREAMING_SNAKE_CASE     )] for i in range(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )]

 return top_left, top_right, bot_left, bot_right

def 			_a  (				SCREAMING_SNAKE_CASE	:				list     ):







 """simple docstring"""



 return len(SCREAMING_SNAKE_CASE     ), len(matrix[0]     )

def 			_a  (				SCREAMING_SNAKE_CASE	:				list     ):







 """simple docstring"""



 print('''\n'''.join(str(SCREAMING_SNAKE_CASE     ) for line in matrix     )     )

def 			_a  (				SCREAMING_SNAKE_CASE	:				list    , SCREAMING_SNAKE_CASE	:				list     ):







 """simple docstring"""



 if matrix_dimensions(SCREAMING_SNAKE_CASE     ) == (2, 2):
  return default_matrix_multiplication(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )

 UpperCamelCase__       ,				UpperCamelCase__       ,				UpperCamelCase__       ,				UpperCamelCase__					:    str          =   split_matrix(SCREAMING_SNAKE_CASE     )
 UpperCamelCase__       ,				UpperCamelCase__       ,				UpperCamelCase__       ,				UpperCamelCase__					:    Dict          =   split_matrix(SCREAMING_SNAKE_CASE     )

 UpperCamelCase__					:    int          =   actual_strassen(SCREAMING_SNAKE_CASE    , matrix_subtraction(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )     )
 UpperCamelCase__					:    Optional[Any]          =   actual_strassen(matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )    , SCREAMING_SNAKE_CASE     )
 UpperCamelCase__					:    Optional[Any]          =   actual_strassen(matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )    , SCREAMING_SNAKE_CASE     )
 UpperCamelCase__					:    List[str]          =   actual_strassen(SCREAMING_SNAKE_CASE    , matrix_subtraction(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )     )
 UpperCamelCase__					:    Any          =   actual_strassen(matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )    , matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )     )
 UpperCamelCase__					:    str          =   actual_strassen(matrix_subtraction(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )    , matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )     )
 UpperCamelCase__					:    Optional[Any]          =   actual_strassen(matrix_subtraction(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )    , matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )     )

 UpperCamelCase__					:    Optional[Any]          =   matrix_addition(matrix_subtraction(matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )    , SCREAMING_SNAKE_CASE     )    , SCREAMING_SNAKE_CASE     )
 UpperCamelCase__					:    List[str]          =   matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )
 UpperCamelCase__					:    Union[str, Any]          =   matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )
 UpperCamelCase__					:    Any          =   matrix_subtraction(matrix_subtraction(matrix_addition(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )    , SCREAMING_SNAKE_CASE     )    , SCREAMING_SNAKE_CASE     )

 # construct the new matrix from our 4 quadrants
 UpperCamelCase__					:    Union[str, Any]          =   []
 for i in range(len(SCREAMING_SNAKE_CASE     )     ):
  new_matrix.append(top_left[i] + top_right[i]     )
 for i in range(len(SCREAMING_SNAKE_CASE     )     ):
  new_matrix.append(bot_left[i] + bot_right[i]     )
 return new_matrix

def 			_a  (				SCREAMING_SNAKE_CASE	:				list    , SCREAMING_SNAKE_CASE	:				list     ):







 """simple docstring"""



 if matrix_dimensions(SCREAMING_SNAKE_CASE     )[1] != matrix_dimensions(SCREAMING_SNAKE_CASE     )[0]:
  UpperCamelCase__					:    Optional[Any]          =   (
      '''Unable to multiply these matrices, please check the dimensions.\n'''
      F"Matrix A: {matrixa}\n"
      F"Matrix B: {matrixa}"
  )
  raise Exception(SCREAMING_SNAKE_CASE     )
 UpperCamelCase__					:    Dict          =   matrix_dimensions(SCREAMING_SNAKE_CASE     )
 UpperCamelCase__					:    Optional[Any]          =   matrix_dimensions(SCREAMING_SNAKE_CASE     )

 if dimensiona[0] == dimensiona[1] and dimensiona[0] == dimensiona[1]:
  return [matrixa, matrixa]

 UpperCamelCase__					:    int          =   max(*SCREAMING_SNAKE_CASE    , *SCREAMING_SNAKE_CASE     )
 UpperCamelCase__					:    Optional[Any]          =   int(math.pow(2    , math.ceil(math.loga(SCREAMING_SNAKE_CASE     )     )     )     )
 UpperCamelCase__					:    List[str]          =   matrixa
 UpperCamelCase__					:    Dict          =   matrixa

 # Adding zeros to the matrices so that the arrays dimensions are the same and also
 # power of 2
 for i in range(0    , SCREAMING_SNAKE_CASE     ):
  if i < dimensiona[0]:
   for _ in range(dimensiona[1]    , SCREAMING_SNAKE_CASE     ):
    new_matrixa[i].append(0     )
  else:
   new_matrixa.append([0] * maxim     )
  if i < dimensiona[0]:
   for _ in range(dimensiona[1]    , SCREAMING_SNAKE_CASE     ):
    new_matrixa[i].append(0     )
  else:
   new_matrixa.append([0] * maxim     )

 UpperCamelCase__					:    Tuple          =   actual_strassen(SCREAMING_SNAKE_CASE    , SCREAMING_SNAKE_CASE     )

 # Removing the additional zeros
 for i in range(0    , SCREAMING_SNAKE_CASE     ):
  if i < dimensiona[0]:
   for _ in range(dimensiona[1]    , SCREAMING_SNAKE_CASE     ):
    final_matrix[i].pop()
  else:
   final_matrix.pop()
 return final_matrix


if __name__ == "__main__":
       __UpperCamelCase       :       Tuple						       =						[
           [2, 3, 4, 5],
           [6, 4, 3, 1],
           [2, 3, 6, 7],
           [3, 1, 2, 4],
           [2, 3, 4, 5],
           [6, 4, 3, 1],
           [2, 3, 6, 7],
           [3, 1, 2, 4],
           [2, 3, 4, 5],
           [6, 2, 3, 1],
       ]
       __UpperCamelCase       :       Any						       =						[[0, 2, 1, 1], [16, 2, 3, 3], [2, 2, 7, 7], [13, 11, 22, 4]]
       print(strassen(matrixa, matrixa))






from collections import OrderedDict
from typing import Mapping

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


__UpperCamelCase       :       Any						       =				logging.get_logger(__name__)

__UpperCamelCase       :       Any						       =				{
    "andreasmadsen/efficient_mlm_m0.40": (
        "https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json"
    ),
}

class       __magic_name__	(     __lowerCAmelCase):
     A:		List[Any]			=      "roberta-prelayernorm"


     def __init__(      self							:     Tuple							,	lowerCamelCase__							:     List[Any]=50265							,	lowerCamelCase__							:     Optional[Any]=768							,	lowerCamelCase__							:     str=12							,	lowerCamelCase__							:     Union[str, Any]=12							,	lowerCamelCase__							:     Dict=3072							,	lowerCamelCase__							:     int="gelu"							,	lowerCamelCase__							:     Tuple=0.1							,	lowerCamelCase__							:     Tuple=0.1							,	lowerCamelCase__							:     List[str]=512							,	lowerCamelCase__							:     int=2							,	lowerCamelCase__							:     Tuple=0.02							,	lowerCamelCase__							:     List[Any]=1E-1_2							,	lowerCamelCase__							:     str=1							,	lowerCamelCase__							:     int=0							,	lowerCamelCase__							:     int=2							,	lowerCamelCase__							:     Union[str, Any]="absolute"							,	lowerCamelCase__							:     Optional[Any]=True							,	lowerCamelCase__							:     Dict=None							,	**lowerCamelCase__							:     Any							,	)  ->      Optional[int]:





      '''simple docstring'''






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

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



class       __magic_name__	(     __lowerCAmelCase):


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





      '''simple docstring'''






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


