


import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard

class   A__							(						unittest.TestCase					):




						def 							__UpperCamelCase			(    self   : List[Any]					)							->       Union[str, Any]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					={
										    '''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''': 76},
										}




						def 							__UpperCamelCase			(    self   : Any					)							->       Tuple:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=ModelCard.from_dict(self.inputs_dict					)
										self.assertTrue(hasattr(_a			,      '''model_details'''					)					)
										self.assertTrue(hasattr(_a			,      '''intended_use'''					)					)
										self.assertTrue(hasattr(_a			,      '''factors'''					)					)
										self.assertTrue(hasattr(_a			,      '''metrics'''					)					)
										self.assertTrue(hasattr(_a			,      '''evaluation_data'''					)					)
										self.assertTrue(hasattr(_a			,      '''training_data'''					)					)
										self.assertTrue(hasattr(_a			,      '''quantitative_analyses'''					)					)
										self.assertTrue(hasattr(_a			,      '''ethical_considerations'''					)					)
										self.assertTrue(hasattr(_a			,      '''caveats_and_recommendations'''					)					)




						def 							__UpperCamelCase			(    self   : str					)							->       List[str]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=ModelCard.from_dict(self.inputs_dict					)
										_SCREAMING_SNAKE_CASE     					=json.loads(modelcard.to_json_string()					)
										for key, value in self.inputs_dict.items():
														self.assertEqual(obj[key]			,      _a					)




						def 							__UpperCamelCase			(    self   : Optional[int]					)							->       Optional[int]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=ModelCard.from_dict(self.inputs_dict					)

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

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




						def 							__UpperCamelCase			(    self   : Union[str, Any]					)							->       int:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=ModelCard.from_dict(self.inputs_dict					)

										with tempfile.TemporaryDirectory() as tmpdirname:
														model_card_first.save_pretrained(_a					)
														_SCREAMING_SNAKE_CASE     					=ModelCard.from_pretrained(_a					)

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



import math







def   lowerCamelCase(				a__):
				_SCREAMING_SNAKE_CASE     					=math.log(2		,10) * number
				_SCREAMING_SNAKE_CASE     					=round((log_number - int(a__))		,15)

				return difference







def   lowerCamelCase(				a__ = 67_8910):
				_SCREAMING_SNAKE_CASE     					=90
				_SCREAMING_SNAKE_CASE     					=0

				_SCREAMING_SNAKE_CASE     					=math.log(1.23		,10)
				_SCREAMING_SNAKE_CASE     					=math.log(1.24		,10)
				_SCREAMING_SNAKE_CASE     					=0

				while position < number:
								_SCREAMING_SNAKE_CASE     					=log_difference(a__)

								if difference >= upper_limit:
												power_iterator += 93

								elif difference < lower_limit:
												power_iterator += 196

								else:
												_SCREAMING_SNAKE_CASE     					=power_iterator
												power_iterator += 196
												position += 1

				return previous_power


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							print(f"""{solution() = }""")