


"""simple docstring"""






import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard


class 			SCREAMING_SNAKE_CASE_  (   unittest.TestCase):




							'''simple docstring'''





							def        UpperCAmelCase (						self)   ->	Tuple:







								'''simple docstring'''




								snake_case__  :						str		=      {
								    "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)   ->	Union[str, Any]:







								'''simple docstring'''




								snake_case__  :						Optional[int]		=      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        UpperCAmelCase (						self)   ->	List[str]:







								'''simple docstring'''




								snake_case__  :						List[str]		=      ModelCard.from_dict(self.inputs_dict)
								snake_case__  :						Any		=      json.loads(modelcard.to_json_string())
								for key, value in self.inputs_dict.items():
									self.assertEqual(obj[key]	,					lowerCamelCase__)




							def        UpperCAmelCase (						self)   ->	Dict:







								'''simple docstring'''




								snake_case__  :						List[str]		=      ModelCard.from_dict(self.inputs_dict)

								with tempfile.TemporaryDirectory() as tmpdirname:
									snake_case__  :						Optional[Any]		=      os.path.join(lowerCamelCase__	,					"modelcard.json")
									model_card_first.to_json_file(lowerCamelCase__)
									snake_case__  :						Dict		=      ModelCard.from_json_file(lowerCamelCase__)

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







							def        UpperCAmelCase (						self)   ->	List[Any]:







								'''simple docstring'''




								snake_case__  :						str		=      ModelCard.from_dict(self.inputs_dict)

								with tempfile.TemporaryDirectory() as tmpdirname:
									model_card_first.save_pretrained(lowerCamelCase__)
									snake_case__  :						Union[str, Any]		=      ModelCard.from_pretrained(lowerCamelCase__)

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









"""simple docstring"""
from __future__ import annotations

import math
import random






def 						lowercase				(	_snake_case		: int	,  _snake_case		: int	,  _snake_case		: int	)	->list[int]:
	"""simple docstring"""





	__snake_case      :		Tuple         =							d * e - 1
	__snake_case      :		List[str]         =							0
	__snake_case      :		Dict         =							0
	while p == 0:
		__snake_case      :		str         =							random.randint(2	,  n - 1	)
		__snake_case      :		int         =							k
		while True:
			if t % 2 == 0:
				__snake_case      :		int         =							t // 2
				__snake_case      :		int         =							(g**t) % n
				__snake_case      :		Optional[Any]         =							math.gcd(x - 1	,  _snake_case	)
				if x > 1 and y > 1:
					__snake_case      :		Tuple         =							y
					__snake_case      :		int         =							n // y
					break  # find the correct factors
			else:
				break  # t is not divisible by 2, break and choose another g
	return sorted([p, q]	)


if __name__ == "__main__":
			import doctest

			doctest.testmod()





