


'''simple docstring'''





from __future__ import annotations

from typing import Any






def 	UpperCAmelCase__(							*_SCREAMING_SNAKE_CASE				:   list[list[int]]   ):






			"""simple docstring"""




			if all(_check_not_integer(_SCREAMING_SNAKE_CASE   ) for m in matrix_s   ):
						for i in matrix_s[1:]:
									_verify_matrix_sizes(matrix_s[0],_SCREAMING_SNAKE_CASE   )
						return [[sum(_SCREAMING_SNAKE_CASE   ) for t in zip(*_SCREAMING_SNAKE_CASE   )] for m in zip(*_SCREAMING_SNAKE_CASE   )]
			raise TypeError('Expected a matrix, got int/list instead'   )






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]],_SCREAMING_SNAKE_CASE				:   list[list[int]]   ):






			"""simple docstring"""




			if (
			    _check_not_integer(_SCREAMING_SNAKE_CASE   )
			    and _check_not_integer(_SCREAMING_SNAKE_CASE   )
			    and _verify_matrix_sizes(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE   )
			):
						return [[i - j for i, j in zip(*_SCREAMING_SNAKE_CASE   )] for m in zip(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE   )]
			raise TypeError('Expected a matrix, got int/list instead'   )






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]],_SCREAMING_SNAKE_CASE				:   int | float   ):






			"""simple docstring"""




			return [[x * n for x in row] for row in matrix]






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]],_SCREAMING_SNAKE_CASE				:   list[list[int]]   ):






			"""simple docstring"""




			if _check_not_integer(_SCREAMING_SNAKE_CASE   ) and _check_not_integer(_SCREAMING_SNAKE_CASE   ):
						__A,  __A=  _verify_matrix_sizes(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE   )

			if cols[0] != rows[1]:
						__A=  (
						    'Cannot multiply matrix of dimensions '
						    f"""({rows[0]},{cols[0]}) and ({rows[1]},{cols[1]})"""
						)
						raise ValueError(_SCREAMING_SNAKE_CASE   )
			return [
			    [sum(m * n for m, n in zip(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE   )   ) for j in zip(*_SCREAMING_SNAKE_CASE   )] for i in matrix_a
			]






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   int   ):






			"""simple docstring"""




			__A=  int(_SCREAMING_SNAKE_CASE   )
			return [[int(row == column   ) for column in range(_SCREAMING_SNAKE_CASE   )] for row in range(_SCREAMING_SNAKE_CASE   )]






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]],_SCREAMING_SNAKE_CASE				:   bool = True   ):






			"""simple docstring"""




			if _check_not_integer(_SCREAMING_SNAKE_CASE   ):
						if return_map:
									return map(_SCREAMING_SNAKE_CASE,zip(*_SCREAMING_SNAKE_CASE   )   )
						else:
									return list(map(_SCREAMING_SNAKE_CASE,zip(*_SCREAMING_SNAKE_CASE   )   )   )
			raise TypeError('Expected a matrix, got int/list instead'   )






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]],_SCREAMING_SNAKE_CASE				:   int,_SCREAMING_SNAKE_CASE				:   int   ):






			"""simple docstring"""




			__A=  matrix[:row] + matrix[row + 1 :]
			return [row[:column] + row[column + 1 :] for row in minor]






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]]   ):






			"""simple docstring"""




			if len(_SCREAMING_SNAKE_CASE   ) == 1:
						return matrix[0][0]

			return sum(
			    x * determinant(minor(_SCREAMING_SNAKE_CASE,0,_SCREAMING_SNAKE_CASE   )   ) * (-1) ** i
			    for i, x in enumerate(matrix[0]   )   )






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]]   ):






			"""simple docstring"""




			__A=  determinant(_SCREAMING_SNAKE_CASE   )
			if det == 0:
						return None

			__A=  [
			    [determinant(minor(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE   )   ) for j in range(len(_SCREAMING_SNAKE_CASE   )   )]
			    for i in range(len(_SCREAMING_SNAKE_CASE   )   )
			]

			__A=  [
			    [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row]   )]
			    for row in range(len(_SCREAMING_SNAKE_CASE   )   )
			]
			__A=  list(transpose(_SCREAMING_SNAKE_CASE   )   )
			return scalar_multiply(_SCREAMING_SNAKE_CASE,1 / det   )






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]]   ):






			"""simple docstring"""




			return not isinstance(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE   ) and not isinstance(matrix[0],_SCREAMING_SNAKE_CASE   )






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]]   ):






			"""simple docstring"""




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






def 	UpperCAmelCase__(							_SCREAMING_SNAKE_CASE				:   list[list[int]],_SCREAMING_SNAKE_CASE				:   list[list[int]]   ):






			"""simple docstring"""




			__A=  _shape(_SCREAMING_SNAKE_CASE   ) + _shape(_SCREAMING_SNAKE_CASE   )
			if shape[0] != shape[3] or shape[1] != shape[2]:
						__A=  (
						    'operands could not be broadcast together with shape '
						    f"""({shape[0], shape[1]}), ({shape[2], shape[3]})"""
						)
						raise ValueError(_SCREAMING_SNAKE_CASE   )
			return (shape[0], shape[2]), (shape[1], shape[3])






def 	UpperCAmelCase__(							):






			"""simple docstring"""




			__A=  [[12, 10], [3, 9]]
			__A=  [[3, 4], [7, 4]]
			__A=  [[11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34], [41, 42, 43, 44]]
			__A=  [[3, 0, 2], [2, 0, -2], [0, 1, 1]]
			print(f"""Add Operation, {add(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE   ) = } \n"""   )
			print(
			    f"""Multiply Operation, {multiply(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE   ) = } \n""",)
			print(f"""Identity: {identity(5   )}\n"""   )
			print(f"""Minor of {matrix_c} = {minor(_SCREAMING_SNAKE_CASE,1,2   )} \n"""   )
			print(f"""Determinant of {matrix_b} = {determinant(_SCREAMING_SNAKE_CASE   )} \n"""   )
			print(f"""Inverse of {matrix_d} = {inverse(_SCREAMING_SNAKE_CASE   )}\n"""   )


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					main()







'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase__      =							logging.get_logger(__name__)

UpperCAmelCase__      =							{
    '''google/mobilebert-uncased''': '''https://huggingface.co/google/mobilebert-uncased/resolve/main/config.json'''
}
class 	a__				(				a_      ):





			'''simple docstring'''

			A	:							int							= MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
			A	:							Optional[int]							= '''mobilebert'''
			def __init__(     self       : Optional[int] ,						lowerCAmelCase_       : str=30_522 ,						lowerCAmelCase_       : List[Any]=512 ,						lowerCAmelCase_       : Optional[int]=24 ,						lowerCAmelCase_       : str=4 ,						lowerCAmelCase_       : List[str]=512 ,						lowerCAmelCase_       : List[str]="relu" ,						lowerCAmelCase_       : Dict=0.0 ,						lowerCAmelCase_       : List[Any]=0.1 ,						lowerCAmelCase_       : Optional[Any]=512 ,						lowerCAmelCase_       : str=2 ,						lowerCAmelCase_       : Dict=0.02 ,						lowerCAmelCase_       : Any=1E-12 ,						lowerCAmelCase_       : List[Any]=0 ,						lowerCAmelCase_       : Union[str, Any]=128 ,						lowerCAmelCase_       : Any=True ,						lowerCAmelCase_       : Optional[Any]=True ,						lowerCAmelCase_       : List[Any]=128 ,						lowerCAmelCase_       : Dict=False ,						lowerCAmelCase_       : Tuple=True ,						lowerCAmelCase_       : Any=4 ,						lowerCAmelCase_       : Optional[Any]="no_norm" ,						lowerCAmelCase_       : Optional[Any]=True ,						lowerCAmelCase_       : Union[str, Any]=None ,						**lowerCAmelCase_       : Union[str, Any] ,						)			->		List[Any]:
						super().__init__(pad_token_id=lowerCAmelCase_ ,						**lowerCAmelCase_  )

						__A=  vocab_size
						__A=  hidden_size
						__A=  num_hidden_layers
						__A=  num_attention_heads
						__A=  hidden_act
						__A=  intermediate_size
						__A=  hidden_dropout_prob
						__A=  attention_probs_dropout_prob
						__A=  max_position_embeddings
						__A=  type_vocab_size
						__A=  initializer_range
						__A=  layer_norm_eps
						__A=  embedding_size
						__A=  trigram_input
						__A=  use_bottleneck
						__A=  intra_bottleneck_size
						__A=  use_bottleneck_attention
						__A=  key_query_shared_bottleneck
						__A=  num_feedforward_networks
						__A=  normalization_type
						__A=  classifier_activation

						if self.use_bottleneck:
									__A=  intra_bottleneck_size
						else:
									__A=  hidden_size

						__A=  classifier_dropout


class 	a__				(				a_      ):





			'''simple docstring'''

			@property
			def 				lowerCAmelCase    (     self       : List[str]  )			->		Mapping[str, Mapping[int, str]]:
						if self.task == "multiple-choice":
									__A=  {0: 'batch', 1: 'choice', 2: 'sequence'}
						else:
									__A=  {0: 'batch', 1: 'sequence'}
						return OrderedDict(
						    [
						        ('input_ids', dynamic_axis),
						        ('attention_mask', dynamic_axis),
						        ('token_type_ids', dynamic_axis),
						    ]  )



