

from maths.prime_check import is_prime






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__      )  ->					int:
	if not isinstance(lowerCamelCase__     ,			lowerCamelCase__      ):
		__lowerCamelCase    :    List[Any] 	=			F"Input value of [number={number}] must be an integer"
		raise TypeError(lowerCamelCase__      )
	if is_prime(lowerCamelCase__      ) and is_prime(number + 2      ):
		return number + 2
	else:
		return -1


if __name__ == "__main__":
					import doctest

					doctest.testmod()







from __future__ import annotations

import unittest

from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow


if is_tf_available():
					from transformers import (
					    AutoConfig,
					    BertConfig,
					    GPTaConfig,
					    TaConfig,
					    TFAutoModel,
					    TFAutoModelForCausalLM,
					    TFAutoModelForMaskedLM,
					    TFAutoModelForPreTraining,
					    TFAutoModelForQuestionAnswering,
					    TFAutoModelForSeqaSeqLM,
					    TFAutoModelForSequenceClassification,
					    TFAutoModelWithLMHead,
					    TFBertForMaskedLM,
					    TFBertForPreTraining,
					    TFBertForQuestionAnswering,
					    TFBertForSequenceClassification,
					    TFBertModel,
					    TFGPTaLMHeadModel,
					    TFRobertaForMaskedLM,
					    TFTaForConditionalGeneration,
					)
					from transformers.models.bert.modeling_tf_bert import TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST
					from transformers.models.gpta.modeling_tf_gpta import TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST
					from transformers.models.ta.modeling_tf_ta import TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST

if is_torch_available():
					from transformers import (
					    AutoModel,
					    AutoModelForCausalLM,
					    AutoModelForMaskedLM,
					    AutoModelForPreTraining,
					    AutoModelForQuestionAnswering,
					    AutoModelForSeqaSeqLM,
					    AutoModelForSequenceClassification,
					    AutoModelWithLMHead,
					    BertForMaskedLM,
					    BertForPreTraining,
					    BertForQuestionAnswering,
					    BertForSequenceClassification,
					    BertModel,
					    GPTaLMHeadModel,
					    RobertaForMaskedLM,
					    TaForConditionalGeneration,
					)






@is_pt_tf_cross_test
class 	A_		(	unittest.TestCase    ):
							@slow
							def    lowerCAmelCase					(		self		:      List[str]):
								# for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
								for model_name in ["bert-base-uncased"]:
									__lowerCamelCase    :    Optional[int] 	=			AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    Tuple 	=			TFAutoModel.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    str 	=			AutoModel.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							@slow
							def    lowerCAmelCase					(		self		:      Optional[int]):
								# for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
								for model_name in ["bert-base-uncased"]:
									__lowerCamelCase    :    str 	=			AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    Tuple 	=			TFAutoModelForPreTraining.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    str 	=			AutoModelForPreTraining.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							@slow
							def    lowerCAmelCase					(		self		:      Optional[int]):
								for model_name in TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
									__lowerCamelCase    :    Union[str, Any] 	=			AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    Union[str, Any] 	=			TFAutoModelForCausalLM.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									__lowerCamelCase	,			__lowerCamelCase    :    Union[str, Any] 	=			TFAutoModelForCausalLM.from_pretrained(
									    SCREAMING_SNAKE_CASE__       ,output_loading_info=SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    List[Any] 	=			AutoModelForCausalLM.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									__lowerCamelCase	,			__lowerCamelCase    :    Any 	=			AutoModelForCausalLM.from_pretrained(
									    SCREAMING_SNAKE_CASE__       ,output_loading_info=SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							@slow
							def    lowerCAmelCase					(		self		:      List[Any]):
								for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
									__lowerCamelCase    :    List[str] 	=			AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    List[str] 	=			TFAutoModelWithLMHead.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    Optional[Any] 	=			AutoModelWithLMHead.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							@slow
							def    lowerCAmelCase					(		self		:      Tuple):
								for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
									__lowerCamelCase    :    Optional[Any] 	=			AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    Optional[int] 	=			TFAutoModelForMaskedLM.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									__lowerCamelCase	,			__lowerCamelCase    :    Dict 	=			TFAutoModelForMaskedLM.from_pretrained(
									    SCREAMING_SNAKE_CASE__       ,output_loading_info=SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    List[Any] 	=			AutoModelForMaskedLM.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									__lowerCamelCase	,			__lowerCamelCase    :    Optional[Any] 	=			AutoModelForMaskedLM.from_pretrained(
									    SCREAMING_SNAKE_CASE__       ,output_loading_info=SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							@slow
							def    lowerCAmelCase					(		self		:      str):
								for model_name in TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
									__lowerCamelCase    :    Dict 	=			AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    Optional[Any] 	=			TFAutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									__lowerCamelCase	,			__lowerCamelCase    :    List[str] 	=			TFAutoModelForSeqaSeqLM.from_pretrained(
									    SCREAMING_SNAKE_CASE__       ,output_loading_info=SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    Any 	=			AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									__lowerCamelCase	,			__lowerCamelCase    :    List[str] 	=			AutoModelForSeqaSeqLM.from_pretrained(
									    SCREAMING_SNAKE_CASE__       ,output_loading_info=SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							@slow
							def    lowerCAmelCase					(		self		:      Optional[Any]):
								# for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
								for model_name in ["bert-base-uncased"]:
									__lowerCamelCase    :    List[Any] 	=			AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    Optional[int] 	=			TFAutoModelForSequenceClassification.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    int 	=			AutoModelForSequenceClassification.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							@slow
							def    lowerCAmelCase					(		self		:      Any):
								# for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
								for model_name in ["bert-base-uncased"]:
									__lowerCamelCase    :    List[Any] 	=			AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    str 	=			TFAutoModelForQuestionAnswering.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

									__lowerCamelCase    :    Optional[int] 	=			AutoModelForQuestionAnswering.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
									self.assertIsNotNone(SCREAMING_SNAKE_CASE__)
									self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							def    lowerCAmelCase					(		self		:      int):
								__lowerCamelCase    :    List[Any] 	=			TFAutoModelWithLMHead.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
								self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
								self.assertEqual(model.num_parameters()       ,1_4_4_1_0)
								self.assertEqual(model.num_parameters(only_trainable=SCREAMING_SNAKE_CASE__)       ,1_4_4_1_0)

								__lowerCamelCase    :    Union[str, Any] 	=			AutoModelWithLMHead.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
								self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
								self.assertEqual(model.num_parameters()       ,1_4_4_1_0)
								self.assertEqual(model.num_parameters(only_trainable=SCREAMING_SNAKE_CASE__)       ,1_4_4_1_0)


							def    lowerCAmelCase					(		self		:      Tuple):
								__lowerCamelCase    :    str 	=			TFAutoModelWithLMHead.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_pt=SCREAMING_SNAKE_CASE__)
								self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
								self.assertEqual(model.num_parameters()       ,1_4_4_1_0)
								self.assertEqual(model.num_parameters(only_trainable=SCREAMING_SNAKE_CASE__)       ,1_4_4_1_0)

								__lowerCamelCase    :    Optional[int] 	=			AutoModelWithLMHead.from_pretrained(SCREAMING_SNAKE_CASE__       ,from_tf=SCREAMING_SNAKE_CASE__)
								self.assertIsInstance(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
								self.assertEqual(model.num_parameters()       ,1_4_4_1_0)
								self.assertEqual(model.num_parameters(only_trainable=SCREAMING_SNAKE_CASE__)       ,1_4_4_1_0)




