
'''simple docstring'''
import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_    )		->		str:
			A_       		=   min(re.search('^ +'					,SCREAMING_SNAKE_CASE_    ).end() if t.startswith(' '    ) else 0 for t in string.splitlines()    )
			return "\n".join([line[indent_level:] for line in string.splitlines() if indent_level < len(SCREAMING_SNAKE_CASE_    )]    )


_SCREAMING_SNAKE_CASE =	"\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n"

_SCREAMING_SNAKE_CASE =	"\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n"


_SCREAMING_SNAKE_CASE =	"\\n# Begin of markdown\n\nSome cool dataset card\n"






class      __UpperCAmelCase							(    unittest.TestCase							):



					'''simple docstring'''





					def 						__snake_case	(  self    :	List[Any])						->       Optional[Any]:
								with tempfile.TemporaryDirectory() as tmp_dir:
											A_       		=   Path(_lowercase) / 'README.md'
											with open(_lowercase			,					'w+') as readme_file:
														readme_file.write(_lowercase)
											A_       		=   DatasetMetadata.from_readme(_lowercase)
											self.assertDictEqual(_lowercase			,					{'language': ['zh', 'en'], 'task_ids': ['sentiment-classification']})

											with open(_lowercase			,					'w+') as readme_file:
														readme_file.write(_lowercase)
											A_       		=   DatasetMetadata.from_readme(_lowercase)
											self.assertDictEqual(_lowercase			,					{})

											with open(_lowercase			,					'w+') as readme_file:
														readme_file.write(_lowercase)
											A_       		=   DatasetMetadata.from_readme(_lowercase)
											self.assertEqual(_lowercase			,					{})



					def 						__snake_case	(  self    :	str)						->       Optional[Any]:
								A_       		=   _dedent(
								    '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            ')
								assert DatasetMetadata.from_yaml_string(_lowercase)

								A_       		=   _dedent(
								    '\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            ')
								with self.assertRaises(_lowercase):
											DatasetMetadata.from_yaml_string(_lowercase)

								A_       		=   _dedent(
								    '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the "Researcher") has requested permission to use the ImageNet database (the "Database") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            ')
								assert DatasetMetadata.from_yaml_string(_lowercase)










'''simple docstring'''
from __future__ import annotations

import sys





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		tuple[int, int]:
			# base cases
			if abs(SCREAMING_SNAKE_CASE_    ) == 1:
						return a, 0
			elif abs(SCREAMING_SNAKE_CASE_    ) == 1:
						return 0, b

			A_		,   A_       		=   a, b
			A_		,   A_       		=   1, 0
			A_		,   A_       		=   0, 1

			while remainder != 0:
						A_       		=   old_remainder // remainder
						A_		,   A_       		=   remainder, old_remainder - quotient * remainder
						A_		,   A_       		=   coeff_a, old_coeff_a - quotient * coeff_a
						A_		,   A_       		=   coeff_b, old_coeff_b - quotient * coeff_b

			# sign correction for negative numbers
			if a < 0:
						A_       		=   -old_coeff_a
			if b < 0:
						A_       		=   -old_coeff_b

			return old_coeff_a, old_coeff_b





def  lowerCamelCase(       )		->		Tuple:
			if len(sys.argv    ) < 3:
						print('2 integer arguments required'    )
						return 1
			A_       		=   int(sys.argv[1]    )
			A_       		=   int(sys.argv[2]    )
			print(extended_euclidean_algorithm(SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )    )
			return 0


if __name__ == "__main__":
							raise SystemExit(main())




