'''simple docstring'''




from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters

def _lowercase	(      )					->       Union[str, Any]:





       """simple docstring"""


       __UpperCAmelCase  :				List[Any]       				=		{
           "repo_name": ["test_repo1", "test_repo2", "test_repo3"],
           "path": ["test_1.py", "test_2.py", "unit_test.py"],
           "content": ["a " * 20, "a " * 30, "b " * 7],
       }
       __UpperCAmelCase  :				Tuple       				=		Dataset.from_dict(lowerCamelCase__						)
       return dataset






class 		__A       (__magic_name__   ):






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				Any       				=		get_dataset()
              __UpperCAmelCase  :				List[Any]       				=		make_duplicate_clusters(UpperCamelCase_				,     0.8_5      )
              self.assertEqual(len(duplicate_clusters[0]      )				,     2      )







       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				Tuple       				=		get_dataset()
              __UpperCAmelCase				, __UpperCAmelCase  :				Tuple       				=		deduplicate_dataset(UpperCamelCase_      )
              self.assertEqual(len(UpperCamelCase_      )				,     2      )
              print(UpperCamelCase_      )
              self.assertEqual(duplicate_clusters[0][0]["copies"]				,     2      )
              self.assertEqual(duplicate_clusters[0][0]["is_extreme"]				,     UpperCamelCase_      )







'''simple docstring'''




from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments

def _lowercase	(      )					->       Dict:





       """simple docstring"""


       __UpperCAmelCase  :				str       				=		HfArgumentParser(lowerCamelCase__						)
       __UpperCAmelCase  :				Optional[Any]       				=		parser.parse_args_into_dataclasses()[0]
       __UpperCAmelCase  :				Any       				=		TensorFlowBenchmark(args=lowerCamelCase__						)
       try:
              __UpperCAmelCase  :				List[Any]       				=		parser.parse_args_into_dataclasses()[0]
       except ValueError as e:
              __UpperCAmelCase  :				str       				=		"Arg --no_{0} is no longer used, please use --no-{0} instead."
              __UpperCAmelCase  :				Tuple       				=		" ".join(str(lowerCamelCase__						).split(" "						)[:-1]						)
              __UpperCAmelCase  :				Any       				=		""
              __UpperCAmelCase  :				List[Any]       				=		eval(str(lowerCamelCase__						).split(" "						)[-1]						)
              __UpperCAmelCase  :				Optional[int]       				=		[]
              for arg in depreciated_args:
                     # arg[2:] removes '--'
                     if arg[2:] in TensorFlowBenchmark.deprecated_args:
                            # arg[5:] removes '--no_'
                            full_error_msg += arg_error_msg.format(arg[5:]						)
                     else:
                            wrong_args.append(lowerCamelCase__						)
              if len(lowerCamelCase__						) > 0:
                     __UpperCAmelCase  :				Union[str, Any]       				=		full_error_msg + begin_error_msg + str(lowerCamelCase__						)
              raise ValueError(lowerCamelCase__						)
       benchmark.run()


if __name__ == "__main__":
   main()






