
def     UpperCAmelCase__							(       __magic_name__						:     list  ):


					'''simple docstring'''

					for insert_index, insert_value in enumerate(collection[1:]  ):
										lowerCAmelCase		:					Union[str, Any]  	=     insert_index
										while insert_index >= 0 and insert_value < collection[insert_index]:
															lowerCAmelCase		:					Optional[int]  	=     collection[insert_index]
															insert_index -= 1
										if insert_index != temp_index:
															lowerCAmelCase		:					str  	=     insert_value
					return collection


if __name__ == "__main__":
		from doctest import testmod

		testmod()

		__SCREAMING_SNAKE_CASE			:   Tuple         =     input('Enter numbers separated by a comma:\n').strip()
		__SCREAMING_SNAKE_CASE			:   List[Any]         =     [int(item) for item in user_input.split(',')]
		print(f"""{insertion_sort(unsorted) = }""")


import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard


class 		__magic_name__   (						unittest.TestCase    ):





		def       _A							(							self    :	Dict				):
							lowerCAmelCase		:					List[Any]  	=     {
							    '''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''': 5_5.1, '''ROUGE-1''': 7_6},
							}





		def       _A							(							self    :	str				):
							lowerCAmelCase		:					Dict  	=     ModelCard.from_dict(self.inputs_dict				)
							self.assertTrue(hasattr(lowerCamelCase__						,  '''model_details'''				)				)
							self.assertTrue(hasattr(lowerCamelCase__						,  '''intended_use'''				)				)
							self.assertTrue(hasattr(lowerCamelCase__						,  '''factors'''				)				)
							self.assertTrue(hasattr(lowerCamelCase__						,  '''metrics'''				)				)
							self.assertTrue(hasattr(lowerCamelCase__						,  '''evaluation_data'''				)				)
							self.assertTrue(hasattr(lowerCamelCase__						,  '''training_data'''				)				)
							self.assertTrue(hasattr(lowerCamelCase__						,  '''quantitative_analyses'''				)				)
							self.assertTrue(hasattr(lowerCamelCase__						,  '''ethical_considerations'''				)				)
							self.assertTrue(hasattr(lowerCamelCase__						,  '''caveats_and_recommendations'''				)				)





		def       _A							(							self    :	Optional[Any]				):
							lowerCAmelCase		:					Tuple  	=     ModelCard.from_dict(self.inputs_dict				)
							lowerCAmelCase		:					Dict  	=     json.loads(modelcard.to_json_string()				)
							for key, value in self.inputs_dict.items():
												self.assertEqual(obj[key]						,  lowerCamelCase__				)





		def       _A							(							self    :	Tuple				):
							lowerCAmelCase		:					Tuple  	=     ModelCard.from_dict(self.inputs_dict				)

							with tempfile.TemporaryDirectory() as tmpdirname:
												lowerCAmelCase		:					str  	=     os.path.join(lowerCamelCase__						,  '''modelcard.json'''				)
												model_card_first.to_json_file(lowerCamelCase__				)
												lowerCAmelCase		:					Dict  	=     ModelCard.from_json_file(lowerCamelCase__				)

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





		def       _A							(							self    :	Union[str, Any]				):
							lowerCAmelCase		:					int  	=     ModelCard.from_dict(self.inputs_dict				)

							with tempfile.TemporaryDirectory() as tmpdirname:
												model_card_first.save_pretrained(lowerCamelCase__				)
												lowerCAmelCase		:					Any  	=     ModelCard.from_pretrained(lowerCamelCase__				)

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