import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard


class 						a__							(   unittest.TestCase		):



			def __SCREAMING_SNAKE_CASE							(						self    ) ->    List[str]:
								__a							=   {
								    'model_details': {
								        'Organization': 'testing',
								        'Model date': 'today',
								        'Model version': 'v2.1, Developed by Test Corp in 2019.',
								        'Architecture': 'Convolutional Neural Network.',
								    },
								    'metrics': 'BLEU and ROUGE-1',
								    'evaluation_data': {
								        'Datasets': {'BLEU': 'My-great-dataset-v1', 'ROUGE-1': 'My-short-dataset-v2.1'},
								        'Preprocessing': 'See details on https://arxiv.org/pdf/1810.03993.pdf',
								    },
								    'training_data': {
								        'Dataset': 'English Wikipedia dump dated 2018-12-01',
								        'Preprocessing': (
								            'Using SentencePiece vocabulary of size 52k tokens. See details on'
								            ' https://arxiv.org/pdf/1810.03993.pdf'
								        ),
								    },
								    'quantitative_analyses': {'BLEU': 55.1, 'ROUGE-1': 7_6},
								}



			def __SCREAMING_SNAKE_CASE							(						self    ) ->    Tuple:
								__a							=   ModelCard.from_dict(self.inputs_dict    )
								self.assertTrue(hasattr(UpperCAmelCase      ,						'model_details'    )    )
								self.assertTrue(hasattr(UpperCAmelCase      ,						'intended_use'    )    )
								self.assertTrue(hasattr(UpperCAmelCase      ,						'factors'    )    )
								self.assertTrue(hasattr(UpperCAmelCase      ,						'metrics'    )    )
								self.assertTrue(hasattr(UpperCAmelCase      ,						'evaluation_data'    )    )
								self.assertTrue(hasattr(UpperCAmelCase      ,						'training_data'    )    )
								self.assertTrue(hasattr(UpperCAmelCase      ,						'quantitative_analyses'    )    )
								self.assertTrue(hasattr(UpperCAmelCase      ,						'ethical_considerations'    )    )
								self.assertTrue(hasattr(UpperCAmelCase      ,						'caveats_and_recommendations'    )    )



			def __SCREAMING_SNAKE_CASE							(						self    ) ->    str:
								__a							=   ModelCard.from_dict(self.inputs_dict    )
								__a							=   json.loads(modelcard.to_json_string()    )
								for key, value in self.inputs_dict.items():
													self.assertEqual(obj[key]      ,						UpperCAmelCase    )



			def __SCREAMING_SNAKE_CASE							(						self    ) ->    List[str]:
								__a							=   ModelCard.from_dict(self.inputs_dict    )

								with tempfile.TemporaryDirectory() as tmpdirname:
													__a							=   os.path.join(UpperCAmelCase      ,						'modelcard.json'    )
													model_card_first.to_json_file(UpperCAmelCase    )
													__a							=   ModelCard.from_json_file(UpperCAmelCase    )

								self.assertEqual(model_card_second.to_dict()      ,						model_card_first.to_dict()    )







			def __SCREAMING_SNAKE_CASE							(						self    ) ->    int:
								__a							=   ModelCard.from_dict(self.inputs_dict    )

								with tempfile.TemporaryDirectory() as tmpdirname:
													model_card_first.save_pretrained(UpperCAmelCase    )
													__a							=   ModelCard.from_pretrained(UpperCAmelCase    )

								self.assertEqual(model_card_second.to_dict()      ,						model_card_first.to_dict()    )





def 							lowerCAmelCase(	__lowerCamelCase = 10**6						):

					if n <= 0:
										raise ValueError('Please enter an integer greater than 0'						)

					__a							=   list(range(n + 1						)						)
					for number in range(2      ,				n + 1						):
										if phi[number] == number:
															phi[number] -= 1
															for multiple in range(number * 2      ,				n + 1      ,				__lowerCamelCase						):
																				__a							=   (phi[multiple] // number) * (number - 1)

					__a							=   1
					for number in range(1      ,				n + 1						):
										if (answer / phi[answer]) < (number / phi[number]):
															__a							=   number

					return answer


if __name__ == "__main__":
	print(solution())




