



'''simple docstring'''







import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE     ):
		SCREAMING_SNAKE_CASE_						:Optional[int]										=      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__     : List[Any]				=   """\
---
language:
- zh
- en
task_ids:
- sentiment-classification
---
# Begin of markdown

Some cool dataset card
"""

SCREAMING_SNAKE_CASE__     : Optional[Any]				=   """\
---
---
# Begin of markdown

Some cool dataset card
"""


SCREAMING_SNAKE_CASE__     : Dict				=   """\
# Begin of markdown

Some cool dataset card
"""





class 				__lowerCAmelCase(							unittest.TestCase      ):






			def 				_lowercase	(   self  :							int	):




					"""simple docstring"""







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

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

							with open(SCREAMING_SNAKE_CASE      ,       'w+'	) as readme_file:
									readme_file.write(SCREAMING_SNAKE_CASE	)
							SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      DatasetMetadata.from_readme(SCREAMING_SNAKE_CASE	)
							self.assertEqual(SCREAMING_SNAKE_CASE      ,       {}	)






			def 				_lowercase	(   self  :							List[str]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:List[Any]										=      _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(SCREAMING_SNAKE_CASE	)

					SCREAMING_SNAKE_CASE_						:Any										=      _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(SCREAMING_SNAKE_CASE	):
							DatasetMetadata.from_yaml_string(SCREAMING_SNAKE_CASE	)

					SCREAMING_SNAKE_CASE_						:Optional[int]										=      _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(SCREAMING_SNAKE_CASE	)





'''simple docstring'''







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     ):
		assert b != 0, "This cannot accept modulo that is == 0"
		if n == 0:
				return 1

		if n % 2 == 1:
				return (bin_exp_mod(SCREAMING_SNAKE_CASE ,		n - 1 ,		SCREAMING_SNAKE_CASE     ) * a) % b

		SCREAMING_SNAKE_CASE_						:List[str]										=      bin_exp_mod(SCREAMING_SNAKE_CASE ,		n / 2 ,		SCREAMING_SNAKE_CASE     )
		return (r * r) % b


if __name__ == "__main__":
							try:
														SCREAMING_SNAKE_CASE__     : Any				=   int(input("""Enter Base : """).strip())
														SCREAMING_SNAKE_CASE__     : str				=   int(input("""Enter Power : """).strip())
														SCREAMING_SNAKE_CASE__     : List[Any]				=   int(input("""Enter Modulo : """).strip())
							except ValueError:
														print("""Invalid literal for integer""")

							print(bin_exp_mod(BASE, POWER, MODULO))
