


from math import sqrt


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (
						    number >= 0
						), "'number' must been an int and positive"

						__SCREAMING_SNAKE_CASE						:     str					=		True

						# 0 and 1 are none primes.
						if number <= 1:
												__SCREAMING_SNAKE_CASE						:     Any					=		False

						for divisor in range(2    ,       int(round(sqrt(lowercase__      )      )      ) + 1      ):
												# if 'number' divisible by 'divisor' then sets 'status'
												# of false and break up the loop.
												if number % divisor == 0:
																		__SCREAMING_SNAKE_CASE						:     List[Any]					=		False
																		break

    # precondition
						assert isinstance(lowercase__    ,       lowercase__      ), "'status' must been from type bool"

						return status


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (n > 2), "'N' must been an int and > 2"

						# beginList: contains all natural numbers from 2 up to N
						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		list(range(2    ,       n + 1      )      )

						__SCREAMING_SNAKE_CASE						:     Optional[int]					=		[]  # this list will be returns.

						# actual sieve of erathostenes
						for i in range(len(lowercase__      )      ):
												for j in range(i + 1    ,       len(lowercase__      )      ):
																		if (begin_list[i] != 0) and (begin_list[j] % begin_list[i] == 0):
																								__SCREAMING_SNAKE_CASE						:     List[Any]					=		0

    # filters actual prime numbers.
						__SCREAMING_SNAKE_CASE						:     Tuple					=		[x for x in begin_list if x != 0]

						# precondition
						assert isinstance(lowercase__    ,       lowercase__      ), "'ans' must been from type list"

						return ans


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (n > 2), "'N' must been an int and > 2"

						__SCREAMING_SNAKE_CASE						:     str					=		[]

						# iterates over all numbers between 2 up to N+1
						# if a number is prime then appends to list 'ans'
						for number in range(2    ,       n + 1      ):
												if is_prime(lowercase__      ):
																		ans.append(lowercase__      )

    # precondition
						assert isinstance(lowercase__    ,       lowercase__      ), "'ans' must been from type list"

						return ans


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and number >= 0, "'number' must been an int and >= 0"

						__SCREAMING_SNAKE_CASE						:     str					=		[]  # this list will be returns of the function.

						# potential prime number factors.

						__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		2

						__SCREAMING_SNAKE_CASE						:     Any					=		number

						if number == 0 or number == 1:
												ans.append(lowercase__      )

						# if 'number' not prime then builds the prime factorization of 'number'
						elif not is_prime(lowercase__      ):
												while quotient != 1:
																		if is_prime(lowercase__      ) and (quotient % factor == 0):
																								ans.append(lowercase__      )
																								quotient /= factor
																		else:
																								factor += 1

						else:
												ans.append(lowercase__      )

						# precondition
						assert isinstance(lowercase__    ,       lowercase__      ), "'ans' must been from type list"

						return ans


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (
						    number >= 0
						), "'number' bust been an int and >= 0"

						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		0

						# prime factorization of 'number'
						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		prime_factorization(lowercase__      )

						__SCREAMING_SNAKE_CASE						:     Tuple					=		max(lowercase__      )

						# precondition
						assert isinstance(lowercase__    ,       lowercase__      ), "'ans' must been from type int"

						return ans


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (
						    number >= 0
						), "'number' bust been an int and >= 0"

						__SCREAMING_SNAKE_CASE						:     int					=		0

						# prime factorization of 'number'
						__SCREAMING_SNAKE_CASE						:     List[Any]					=		prime_factorization(lowercase__      )

						__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		min(lowercase__      )

						# precondition
						assert isinstance(lowercase__    ,       lowercase__      ), "'ans' must been from type int"

						return ans


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ), "'number' must been an int"
						assert isinstance(number % 2 == 0    ,       lowercase__      ), "compare bust been from type bool"

						return number % 2 == 0


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ), "'number' must been an int"
						assert isinstance(number % 2 != 0    ,       lowercase__      ), "compare bust been from type bool"

						return number % 2 != 0


def        _UpperCamelCase							(      lowercase__      ):
						assert (
						    isinstance(lowercase__    ,       lowercase__      ) and (number > 2) and is_even(lowercase__      )
						), "'number' must been an int, even and > 2"

						__SCREAMING_SNAKE_CASE						:     Tuple					=		[]  # this list will returned

						# creates a list of prime numbers between 2 up to 'number'
						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		get_prime_numbers(lowercase__      )
						__SCREAMING_SNAKE_CASE						:     Tuple					=		len(lowercase__      )

						# run variable for while-loops.
						__SCREAMING_SNAKE_CASE						:     List[str]					=		0
						__SCREAMING_SNAKE_CASE						:     Tuple					=		None

						# exit variable. for break up the loops
						__SCREAMING_SNAKE_CASE						:     Any					=		True

						while i < len_pn and loop:
												__SCREAMING_SNAKE_CASE						:     Tuple					=		i + 1

												while j < len_pn and loop:
																		if prime_numbers[i] + prime_numbers[j] == number:
																								__SCREAMING_SNAKE_CASE						:     List[str]					=		False
																								ans.append(prime_numbers[i]      )
																								ans.append(prime_numbers[j]      )

																		j += 1

												i += 1

						# precondition
						assert (
						    isinstance(lowercase__    ,       lowercase__      )
						    and (len(lowercase__      ) == 2)
						    and (ans[0] + ans[1] == number)
						    and is_prime(ans[0]      )
						    and is_prime(ans[1]      )
						), "'ans' must contains two primes. And sum of elements must been eq 'number'"

						return ans


def        _UpperCamelCase							(      lowercase__    ,       lowercase__      ):
						assert (
						    isinstance(lowercase__    ,       lowercase__      )
						    and isinstance(lowercase__    ,       lowercase__      )
						    and (numbera >= 0)
						    and (numbera >= 0)
						), "'number1' and 'number2' must been positive integer."

						__SCREAMING_SNAKE_CASE						:     Any					=		0

						while numbera != 0:
												__SCREAMING_SNAKE_CASE						:     List[Any]					=		numbera % numbera
												__SCREAMING_SNAKE_CASE						:     Optional[int]					=		numbera
												__SCREAMING_SNAKE_CASE						:     Optional[int]					=		rest

						# precondition
						assert isinstance(lowercase__    ,       lowercase__      ) and (
						    numbera >= 0
						), "'number' must been from type int and positive"

						return numbera


def        _UpperCamelCase							(      lowercase__    ,       lowercase__      ):
						assert (
						    isinstance(lowercase__    ,       lowercase__      )
						    and isinstance(lowercase__    ,       lowercase__      )
						    and (numbera >= 1)
						    and (numbera >= 1)
						), "'number1' and 'number2' must been positive integer."

						__SCREAMING_SNAKE_CASE						:     Dict					=		1  # actual answer that will be return.

						# for kgV (x,1)
						if numbera > 1 and numbera > 1:
												# builds the prime factorization of 'number1' and 'number2'
												__SCREAMING_SNAKE_CASE						:     Any					=		prime_factorization(lowercase__      )
												__SCREAMING_SNAKE_CASE						:     Dict					=		prime_factorization(lowercase__      )

						elif numbera == 1 or numbera == 1:
												__SCREAMING_SNAKE_CASE						:     List[str]					=		[]
												__SCREAMING_SNAKE_CASE						:     List[Any]					=		[]
												__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		max(lowercase__    ,       lowercase__      )

						__SCREAMING_SNAKE_CASE						:     int					=		0
						__SCREAMING_SNAKE_CASE						:     List[str]					=		0

						__SCREAMING_SNAKE_CASE						:     Any					=		[]  # captured numbers int both 'primeFac1' and 'primeFac2'

						# iterates through primeFac1
						for n in prime_fac_a:
												if n not in done:
																		if n in prime_fac_a:
																								__SCREAMING_SNAKE_CASE						:     int					=		prime_fac_a.count(lowercase__      )
																								__SCREAMING_SNAKE_CASE						:     str					=		prime_fac_a.count(lowercase__      )

																								for _ in range(max(lowercase__    ,       lowercase__      )      ):
																														ans *= n

																		else:
																								__SCREAMING_SNAKE_CASE						:     str					=		prime_fac_a.count(lowercase__      )

																								for _ in range(lowercase__      ):
																														ans *= n

																		done.append(lowercase__      )

    # iterates through primeFac2
						for n in prime_fac_a:
												if n not in done:
																		__SCREAMING_SNAKE_CASE						:     str					=		prime_fac_a.count(lowercase__      )

																		for _ in range(lowercase__      ):
																								ans *= n

																		done.append(lowercase__      )

    # precondition
						assert isinstance(lowercase__    ,       lowercase__      ) and (
						    ans >= 0
						), "'ans' must been from type int and positive"

						return ans


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (n >= 0), "'number' must been a positive int"

						__SCREAMING_SNAKE_CASE						:     int					=		0
						__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		2  # this variable holds the answer

						while index < n:
												index += 1

												ans += 1  # counts to the next number

												# if ans not prime then
												# runs to the next prime number.
												while not is_prime(lowercase__      ):
																		ans += 1

    # precondition
						assert isinstance(lowercase__    ,       lowercase__      ) and is_prime(
						    lowercase__      ), "'ans' must been a prime number and from type int"

						return ans


def        _UpperCamelCase							(      lowercase__    ,       lowercase__      ):
						assert (
						    is_prime(lowercase__      ) and is_prime(lowercase__      ) and (p_number_a < p_number_a)
						), "The arguments must been prime numbers and 'pNumber1' < 'pNumber2'"

						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		p_number_a + 1  # jump to the next number

						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		[]  # this list will be returns.

						# if number is not prime then
						# fetch the next prime number.
						while not is_prime(lowercase__      ):
												number += 1

						while number < p_number_a:
												ans.append(lowercase__      )

												number += 1

												# fetch the next prime number.
												while not is_prime(lowercase__      ):
																		number += 1

    # precondition
						assert (
						    isinstance(lowercase__    ,       lowercase__      )
						    and ans[0] != p_number_a
						    and ans[len(lowercase__      ) - 1] != p_number_a
						), "'ans' must been a list without the arguments"

						# 'ans' contains not 'pNumber1' and 'pNumber2' !
						return ans


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (n >= 1), "'n' must been int and >= 1"

						__SCREAMING_SNAKE_CASE						:     List[str]					=		[]  # will be returned.

						for divisor in range(1    ,       n + 1      ):
												if n % divisor == 0:
																		ans.append(lowercase__      )

    # precondition
						assert ans[0] == 1 and ans[len(lowercase__      ) - 1] == n, "Error in function getDivisiors(...)"

						return ans


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (
						    number > 1
						), "'number' must been an int and >= 1"

						__SCREAMING_SNAKE_CASE						:     str					=		get_divisors(lowercase__      )

						# precondition
						assert (
						    isinstance(lowercase__    ,       lowercase__      )
						    and (divisors[0] == 1)
						    and (divisors[len(lowercase__      ) - 1] == number)
						), "Error in help-function getDivisiors(...)"

						# summed all divisors up to 'number' (exclusive), hence [:-1]
						return sum(divisors[:-1]      ) == number


def        _UpperCamelCase							(      lowercase__    ,       lowercase__      ):
						assert (
						    isinstance(lowercase__    ,       lowercase__      )
						    and isinstance(lowercase__    ,       lowercase__      )
						    and (denominator != 0)
						), "The arguments must been from type int and 'denominator' != 0"

						# build the greatest common divisor of numerator and denominator.
						__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		gcd(abs(lowercase__      )    ,       abs(lowercase__      )      )

						# precondition
						assert (
						    isinstance(lowercase__    ,       lowercase__      )
						    and (numerator % gcd_of_fraction == 0)
						    and (denominator % gcd_of_fraction == 0)
						), "Error in function gcd(...,...)"

						return (numerator // gcd_of_fraction, denominator // gcd_of_fraction)


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (n >= 0), "'n' must been a int and >= 0"

						__SCREAMING_SNAKE_CASE						:     Any					=		1  # this will be return.

						for factor in range(1    ,       n + 1      ):
												ans *= factor

						return ans


def        _UpperCamelCase							(      lowercase__      ):
						assert isinstance(lowercase__    ,       lowercase__      ) and (n >= 0), "'n' must been an int and >= 0"

						__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		0
						__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		1
						__SCREAMING_SNAKE_CASE						:     Optional[int]					=		1  # this will be return

						for _ in range(n - 1      ):
												__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		ans
												ans += fiba
												__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		tmp

						return ans





import unittest

from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device

from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
						import torch

						from transformers import (
						    MPNetForMaskedLM,
						    MPNetForMultipleChoice,
						    MPNetForQuestionAnswering,
						    MPNetForSequenceClassification,
						    MPNetForTokenClassification,
						    MPNetModel,
						)



class 				__snake_case						:




							def __init__(       self     :       Tuple				,				A_     :       Any				,				A_     :       Tuple=1_3				,				A_     :       str=7				,				A_     :       Any=True				,				A_     :       Union[str, Any]=True				,				A_     :       int=False				,				A_     :       int=True				,				A_     :       List[Any]=9_9				,				A_     :       Dict=6_4				,				A_     :       int=5				,				A_     :       List[Any]=4				,				A_     :       Optional[Any]=6_4				,				A_     :       str="gelu"				,				A_     :       Union[str, Any]=0.1				,				A_     :       List[Any]=0.1				,				A_     :       Any=5_1_2				,				A_     :       Union[str, Any]=1_6				,				A_     :       str=2				,				A_     :       Any=0.02				,				A_     :       str=3				,				A_     :       Optional[int]=4				,				A_     :       int=None				,				):
									lowerCAmelCase_			:     List[Any]									= parent
									lowerCAmelCase_			:     List[Any]									= batch_size
									lowerCAmelCase_			:     List[Any]									= seq_length
									lowerCAmelCase_			:     int									= is_training
									lowerCAmelCase_			:     Union[str, Any]									= use_input_mask
									lowerCAmelCase_			:     Tuple									= use_token_type_ids
									lowerCAmelCase_			:     List[Any]									= use_labels
									lowerCAmelCase_			:     int									= vocab_size
									lowerCAmelCase_			:     Union[str, Any]									= hidden_size
									lowerCAmelCase_			:     Optional[Any]									= num_hidden_layers
									lowerCAmelCase_			:     List[str]									= num_attention_heads
									lowerCAmelCase_			:     List[str]									= intermediate_size
									lowerCAmelCase_			:     int									= hidden_act
									lowerCAmelCase_			:     List[str]									= hidden_dropout_prob
									lowerCAmelCase_			:     Optional[int]									= attention_probs_dropout_prob
									lowerCAmelCase_			:     Optional[Any]									= max_position_embeddings
									lowerCAmelCase_			:     Union[str, Any]									= type_vocab_size
									lowerCAmelCase_			:     Any									= type_sequence_label_size
									lowerCAmelCase_			:     Optional[int]									= initializer_range
									lowerCAmelCase_			:     str									= num_labels
									lowerCAmelCase_			:     List[str]									= num_choices
									lowerCAmelCase_			:     Optional[Any]									= scope




							def    UpperCAmelCase__			(       self     :       Dict):
									return MPNetConfig.from_pretrained('''microsoft/mpnet-base''')




							def    UpperCAmelCase__			(       self     :       int):
									lowerCAmelCase_			:     Union[str, Any]									= ids_tensor([self.batch_size, self.seq_length]				,				self.vocab_size)

									lowerCAmelCase_			:     int									= None
									if self.use_input_mask:
											lowerCAmelCase_			:     List[str]									= random_attention_mask([self.batch_size, self.seq_length])

									lowerCAmelCase_			:     Any									= None
									lowerCAmelCase_			:     Optional[int]									= None
									lowerCAmelCase_			:     Optional[Any]									= None
									if self.use_labels:
											lowerCAmelCase_			:     Any									= ids_tensor([self.batch_size]				,				self.type_sequence_label_size)
											lowerCAmelCase_			:     List[Any]									= ids_tensor([self.batch_size, self.seq_length]				,				self.num_labels)
											lowerCAmelCase_			:     Optional[Any]									= ids_tensor([self.batch_size]				,				self.num_choices)

									lowerCAmelCase_			:     List[str]									= self.get_config()
									return config, input_ids, input_mask, sequence_labels, token_labels, choice_labels




							def    UpperCAmelCase__			(       self     :       Any):
									return MPNetConfig(
									    vocab_size=self.vocab_size				,				hidden_size=self.hidden_size				,				num_hidden_layers=self.num_hidden_layers				,				num_attention_heads=self.num_attention_heads				,				intermediate_size=self.intermediate_size				,				hidden_act=self.hidden_act				,				hidden_dropout_prob=self.hidden_dropout_prob				,				attention_probs_dropout_prob=self.attention_probs_dropout_prob				,				max_position_embeddings=self.max_position_embeddings				,				initializer_range=self.initializer_range				,				)




							def    UpperCAmelCase__			(       self     :       Dict				,				A_     :       Dict				,				A_     :       int				,				A_     :       Tuple				,				A_     :       List[str]				,				A_     :       str				,				A_     :       List[Any]):
									lowerCAmelCase_			:     int									= MPNetModel(config=A_)
									model.to(A_)
									model.eval()
									lowerCAmelCase_			:     Any									= model(A_				,				A_)
									lowerCAmelCase_			:     Union[str, Any]									= model(A_)
									self.parent.assertEqual(result.last_hidden_state.shape				,				(self.batch_size, self.seq_length, self.hidden_size))
									self.parent.assertEqual(result.pooler_output.shape				,				(self.batch_size, self.hidden_size))




							def    UpperCAmelCase__			(       self     :       List[str]				,				A_     :       Union[str, Any]				,				A_     :       List[Any]				,				A_     :       Optional[int]				,				A_     :       Optional[Any]				,				A_     :       Optional[int]				,				A_     :       Any):
									lowerCAmelCase_			:     Any									= MPNetForQuestionAnswering(config=A_)
									model.to(A_)
									model.eval()
									lowerCAmelCase_			:     int									= model(
									    A_				,				attention_mask=A_				,				start_positions=A_				,				end_positions=A_				,				)
									self.parent.assertEqual(result.start_logits.shape				,				(self.batch_size, self.seq_length))
									self.parent.assertEqual(result.end_logits.shape				,				(self.batch_size, self.seq_length))




							def    UpperCAmelCase__			(       self     :       Optional[Any]				,				A_     :       Tuple				,				A_     :       List[str]				,				A_     :       Optional[Any]				,				A_     :       Dict				,				A_     :       Union[str, Any]				,				A_     :       Tuple):
									lowerCAmelCase_			:     Tuple									= self.num_labels
									lowerCAmelCase_			:     Any									= MPNetForSequenceClassification(A_)
									model.to(A_)
									model.eval()
									lowerCAmelCase_			:     Dict									= model(A_				,				attention_mask=A_				,				labels=A_)
									self.parent.assertEqual(result.logits.shape				,				(self.batch_size, self.num_labels))




							def    UpperCAmelCase__			(       self     :       Union[str, Any]				,				A_     :       Tuple				,				A_     :       Dict				,				A_     :       Tuple				,				A_     :       Dict				,				A_     :       List[str]				,				A_     :       List[Any]):
									lowerCAmelCase_			:     int									= self.num_choices
									lowerCAmelCase_			:     List[str]									= MPNetForMultipleChoice(config=A_)
									model.to(A_)
									model.eval()
									lowerCAmelCase_			:     Optional[Any]									= input_ids.unsqueeze(1).expand(-1				,				self.num_choices				,				-1).contiguous()
									lowerCAmelCase_			:     int									= input_mask.unsqueeze(1).expand(-1				,				self.num_choices				,				-1).contiguous()
									lowerCAmelCase_			:     Optional[int]									= model(
									    A_				,				attention_mask=A_				,				labels=A_				,				)
									self.parent.assertEqual(result.logits.shape				,				(self.batch_size, self.num_choices))




							def    UpperCAmelCase__			(       self     :       Optional[Any]				,				A_     :       Any				,				A_     :       int				,				A_     :       Any				,				A_     :       List[Any]				,				A_     :       Any				,				A_     :       Union[str, Any]):
									lowerCAmelCase_			:     int									= self.num_labels
									lowerCAmelCase_			:     Tuple									= MPNetForTokenClassification(config=A_)
									model.to(A_)
									model.eval()
									lowerCAmelCase_			:     Optional[int]									= model(A_				,				attention_mask=A_				,				labels=A_)
									self.parent.assertEqual(result.logits.shape				,				(self.batch_size, self.seq_length, self.num_labels))







							def    UpperCAmelCase__			(       self     :       Union[str, Any]):
									lowerCAmelCase_			:     List[Any]									= self.prepare_config_and_inputs()
									((lowerCAmelCase_)					,  (lowerCAmelCase_)					,  (lowerCAmelCase_)					,  (lowerCAmelCase_)					,  (lowerCAmelCase_)					,  (lowerCAmelCase_))			:     Union[str, Any]									= config_and_inputs
									lowerCAmelCase_			:     List[Any]									= {'''input_ids''': input_ids, '''attention_mask''': input_mask}
									return config, inputs_dict





@require_torch
class 				__snake_case						(     UpperCamelCase_						,UpperCamelCase_						,unittest.TestCase						):
							_a			      = (
							    (
							        MPNetForMaskedLM,
							        MPNetForMultipleChoice,
							        MPNetForQuestionAnswering,
							        MPNetForSequenceClassification,
							        MPNetForTokenClassification,
							        MPNetModel,
							    )
							    if is_torch_available()
							    else ()
							)
							_a			      = (
							    {
							        '''feature-extraction''': MPNetModel,
							        '''fill-mask''': MPNetForMaskedLM,
							        '''question-answering''': MPNetForQuestionAnswering,
							        '''text-classification''': MPNetForSequenceClassification,
							        '''token-classification''': MPNetForTokenClassification,
							        '''zero-shot''': MPNetForSequenceClassification,
							    }
							    if is_torch_available()
							    else {}
							)
							_a			      = False
							_a			      = True




							def    UpperCAmelCase__			(       self     :       Union[str, Any]):
									lowerCAmelCase_			:     List[Any]									= MPNetModelTester(self)
									lowerCAmelCase_			:     Optional[Any]									= ConfigTester(self				,				config_class=A_				,				hidden_size=3_7)




							def    UpperCAmelCase__			(       self     :       Any):
									self.config_tester.run_common_tests()




							def    UpperCAmelCase__			(       self     :       List[Any]):
									lowerCAmelCase_			:     int									= self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_mpnet_model(*A_)




							def    UpperCAmelCase__			(       self     :       Tuple):
									lowerCAmelCase_			:     Optional[int]									= self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_mpnet_for_sequence_classification(*A_)




							def    UpperCAmelCase__			(       self     :       str):
									lowerCAmelCase_			:     Dict									= self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_mpnet_for_multiple_choice(*A_)




							def    UpperCAmelCase__			(       self     :       int):
									lowerCAmelCase_			:     Dict									= self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_mpnet_for_token_classification(*A_)







							def    UpperCAmelCase__			(       self     :       str):
									lowerCAmelCase_			:     Any									= self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_mpnet_for_question_answering(*A_)





@require_torch
class 				__snake_case						(     unittest.TestCase						):




							@slow
							def    UpperCAmelCase__			(       self     :       Tuple):
									lowerCAmelCase_			:     Union[str, Any]									= MPNetModel.from_pretrained('''microsoft/mpnet-base''')
									lowerCAmelCase_			:     Optional[Any]									= torch.tensor([[0, 3_4_5, 2_3_2, 3_2_8, 7_4_0, 1_4_0, 1_6_9_5, 6_9, 6_0_7_8, 1_5_8_8, 2]])
									lowerCAmelCase_			:     Union[str, Any]									= model(A_)[0]
									lowerCAmelCase_			:     Optional[int]									= torch.Size((1, 1_1, 7_6_8))
									self.assertEqual(output.shape				,				A_)
									lowerCAmelCase_			:     Tuple									= torch.tensor(
									    [[[-0.0550, 0.1943, -0.0740], [-0.0562, 0.2211, -0.0579], [-0.0437, 0.3337, -0.0641]]])
									# compare the actual values for a slice.
									self.assertTrue(torch.allclose(output[:, :3, :3]				,				A_				,				atol=1e-4))





