



from __future__ import annotations

from typing import Any


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


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


def     UpperCamelCase(						__UpperCamelCase							:	list[list[int]]  ,__UpperCamelCase							:	int | float				):
		return [[x * n for x in row] for row in matrix]


def     UpperCamelCase(						__UpperCamelCase							:	list[list[int]]  ,__UpperCamelCase							:	list[list[int]]				):
		if _check_not_integer(__UpperCamelCase				) and _check_not_integer(__UpperCamelCase				):
				lowerCAmelCase_      ,						lowerCAmelCase_    :  Any             =				_verify_matrix_sizes(__UpperCamelCase  ,__UpperCamelCase				)

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


def     UpperCamelCase(						__UpperCamelCase							:	int				):
		lowerCAmelCase_    :  Optional[int]             =				int(__UpperCamelCase				)
		return [[int(row == column				) for column in range(__UpperCamelCase				)] for row in range(__UpperCamelCase				)]


def     UpperCamelCase(						__UpperCamelCase							:	list[list[int]]  ,__UpperCamelCase							:	bool = True				):
		if _check_not_integer(__UpperCamelCase				):
				if return_map:
						return map(__UpperCamelCase  ,zip(*__UpperCamelCase				)				)
				else:
						return list(map(__UpperCamelCase  ,zip(*__UpperCamelCase				)				)				)
		raise TypeError('''Expected a matrix, got int/list instead'''				)


def     UpperCamelCase(						__UpperCamelCase							:	list[list[int]]  ,__UpperCamelCase							:	int  ,__UpperCamelCase							:	int				):
		lowerCAmelCase_    :  List[Any]             =				matrix[:row] + matrix[row + 1 :]
		return [row[:column] + row[column + 1 :] for row in minor]


def     UpperCamelCase(						__UpperCamelCase							:	list[list[int]]				):
		if len(__UpperCamelCase				) == 1:
				return matrix[0][0]

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


def     UpperCamelCase(						__UpperCamelCase							:	list[list[int]]				):
		lowerCAmelCase_    :  Optional[Any]             =				determinant(__UpperCamelCase				)
		if det == 0:
				return None

		lowerCAmelCase_    :  Union[str, Any]             =				[
		    [determinant(minor(__UpperCamelCase  ,__UpperCamelCase  ,__UpperCamelCase				)				) for j in range(len(__UpperCamelCase				)				)]
		    for i in range(len(__UpperCamelCase				)				)
		]

		lowerCAmelCase_    :  str             =				[
		    [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row]				)]
		    for row in range(len(__UpperCamelCase				)				)
		]
		lowerCAmelCase_    :  Any             =				list(transpose(__UpperCamelCase				)				)
		return scalar_multiply(__UpperCamelCase  ,1 / det				)


def     UpperCamelCase(						__UpperCamelCase							:	list[list[int]]				):
		return not isinstance(__UpperCamelCase  ,__UpperCamelCase				) and not isinstance(matrix[0]  ,__UpperCamelCase				)


def     UpperCamelCase(						__UpperCamelCase							:	list[list[int]]				):
		return len(__UpperCamelCase				), len(matrix[0]				)


def     UpperCamelCase(						__UpperCamelCase							:	list[list[int]]  ,__UpperCamelCase							:	list[list[int]]				):
		lowerCAmelCase_    :  Optional[int]             =				_shape(__UpperCamelCase				) + _shape(__UpperCamelCase				)
		if shape[0] != shape[3] or shape[1] != shape[2]:
				lowerCAmelCase_    :  List[Any]             =				(
				    '''operands could not be broadcast together with shape '''
				    f"""({shape[0], shape[1]}), ({shape[2], shape[3]})"""
				)
				raise ValueError(__UpperCamelCase				)
		return (shape[0], shape[2]), (shape[1], shape[3])


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


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()










from collections import OrderedDict
from typing import Mapping

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


A__						:						Dict          =      logging.get_logger(__name__)

A__						:						List[str]          =      {
    '''google/electra-small-generator''': '''https://huggingface.co/google/electra-small-generator/resolve/main/config.json''',
    '''google/electra-base-generator''': '''https://huggingface.co/google/electra-base-generator/resolve/main/config.json''',
    '''google/electra-large-generator''': '''https://huggingface.co/google/electra-large-generator/resolve/main/config.json''',
    '''google/electra-small-discriminator''': (
        '''https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'''
    ),
    '''google/electra-base-discriminator''': (
        '''https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'''
    ),
    '''google/electra-large-discriminator''': (
        '''https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'''
    ),
}



class        __snake_case		(  UpperCamelCase_		):
							_a       =				'''electra'''




							def __init__( self  : Dict       ,       A_  : Dict=3_0_5_2_2       ,       A_  : List[Any]=1_2_8       ,       A_  : Dict=2_5_6       ,       A_  : Any=1_2       ,       A_  : Optional[Any]=4       ,       A_  : Optional[int]=1_0_2_4       ,       A_  : Optional[int]="gelu"       ,       A_  : str=0.1       ,       A_  : Optional[int]=0.1       ,       A_  : str=5_1_2       ,       A_  : Optional[int]=2       ,       A_  : Dict=0.02       ,       A_  : Union[str, Any]=1e-12       ,       A_  : List[Any]="first"       ,       A_  : List[str]=True       ,       A_  : List[str]="gelu"       ,       A_  : Any=0.1       ,       A_  : int=0       ,       A_  : Optional[Any]="absolute"       ,       A_  : Optional[int]=True       ,       A_  : str=None       ,       **A_  : List[Any]       ,       ):
									super().__init__(pad_token_id=A_       ,       **A_)

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

									lowerCAmelCase_    :  Union[str, Any]             =				summary_type
									lowerCAmelCase_    :  str             =				summary_use_proj
									lowerCAmelCase_    :  str             =				summary_activation
									lowerCAmelCase_    :  List[Any]             =				summary_last_dropout
									lowerCAmelCase_    :  Optional[Any]             =				position_embedding_type
									lowerCAmelCase_    :  List[Any]             =				use_cache
									lowerCAmelCase_    :  Any             =				classifier_dropout





class        __snake_case		(  UpperCamelCase_		):




							@property
							def      UpperCAmelCase__    ( self  : Union[str, Any]):
									if self.task == "multiple-choice":
											lowerCAmelCase_    :  Any             =				{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
									else:
											lowerCAmelCase_    :  Union[str, Any]             =				{0: '''batch''', 1: '''sequence'''}
									return OrderedDict(
									    [
									        ('''input_ids''', dynamic_axis),
									        ('''attention_mask''', dynamic_axis),
									        ('''token_type_ids''', dynamic_axis),
									    ])





