




"""simple docstring"""

import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard
class     A__      (      unittest.TestCase     ):




	def 							a_		(   self  :	List[str]	)					-> Tuple:
						__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 							a_		(   self  :	Optional[int]	)					-> Optional[int]:
						__snake_case          =	ModelCard.from_dict(self.inputs_dict	)
						self.assertTrue(hasattr(lowercase      ,    """model_details"""	)	)
						self.assertTrue(hasattr(lowercase      ,    """intended_use"""	)	)
						self.assertTrue(hasattr(lowercase      ,    """factors"""	)	)
						self.assertTrue(hasattr(lowercase      ,    """metrics"""	)	)
						self.assertTrue(hasattr(lowercase      ,    """evaluation_data"""	)	)
						self.assertTrue(hasattr(lowercase      ,    """training_data"""	)	)
						self.assertTrue(hasattr(lowercase      ,    """quantitative_analyses"""	)	)
						self.assertTrue(hasattr(lowercase      ,    """ethical_considerations"""	)	)
						self.assertTrue(hasattr(lowercase      ,    """caveats_and_recommendations"""	)	)




	def 							a_		(   self  :	Optional[Any]	)					-> str:
						__snake_case          =	ModelCard.from_dict(self.inputs_dict	)
						__snake_case          =	json.loads(modelcard.to_json_string()	)
						for key, value in self.inputs_dict.items():
											self.assertEqual(obj[key]      ,    lowercase	)




	def 							a_		(   self  :	Tuple	)					-> Optional[int]:
						__snake_case          =	ModelCard.from_dict(self.inputs_dict	)

						with tempfile.TemporaryDirectory() as tmpdirname:
											__snake_case          =	os.path.join(lowercase      ,    """modelcard.json"""	)
											model_card_first.to_json_file(lowercase	)
											__snake_case          =	ModelCard.from_json_file(lowercase	)

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




	def 							a_		(   self  :	Optional[Any]	)					-> Optional[Any]:
						__snake_case          =	ModelCard.from_dict(self.inputs_dict	)

						with tempfile.TemporaryDirectory() as tmpdirname:
											model_card_first.save_pretrained(lowercase	)
											__snake_case          =	ModelCard.from_pretrained(lowercase	)

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








"""simple docstring"""

from functools import lru_cache




@lru_cache
def       snake_case__	(       lowerCAmelCase   :		int		):
					if not isinstance(lowerCAmelCase				,					lowerCAmelCase		):
										raise TypeError("""k must be an integer."""		)
					if k < 0:
										raise ValueError("""k integer must be greater or equal to zero."""		)
					if k == 0:
										return 0
					elif k == 1:
										return 1
					else:
										return fibonacci(k - 1		) + fibonacci(k - 2		)




def       snake_case__	(       lowerCAmelCase   :		list				,					lowerCAmelCase   :		int		):
					__snake_case          =	len(lowerCAmelCase		)
					# Find m such that F_m >= n where F_i is the i_th fibonacci number.
					__snake_case          =	0
					while True:
										if fibonacci(lowerCAmelCase		) >= len_list:
															__snake_case          =	i
															break
										i += 1
					__snake_case          =	0
					while fibb_k > 0:
										__snake_case          =	min(
										    offset + fibonacci(fibb_k - 1		)				,					len_list - 1		)  # Prevent out of range
										__snake_case          =	arr[index_k]
										if item_k_1 == val:
															return index_k
										elif val < item_k_1:
															fibb_k -= 1
										elif val > item_k_1:
															offset += fibonacci(fibb_k - 1		)
															fibb_k -= 2
					else:
										return -1


if __name__ == "__main__":
		import doctest

		doctest.testmod()


