






import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property



@unittest.skipUnless(os.path.exists(_snake_case			) ,  '''Tatoeba directory does not exist.'''			)
class   lowerCamelCase      (unittest.TestCase			):







		'''simple docstring'''



		@cached_property
		def 					__UpperCAmelCase			(							self   )	->							str:
							UpperCAmelCase_    :      Any            =						tempfile.mkdtemp()
							return TatoebaConverter(save_dir=_UpperCamelCase   )



		@slow
		def 					__UpperCAmelCase			(							self   )	->							Optional[Any]:
							self.resolver.convert_models(['heb-eng']   )



		@slow
		def 					__UpperCAmelCase			(							self   )	->							Tuple:
							UpperCAmelCase_       ,  UpperCAmelCase_    :      Any            =						self.resolver.write_model_card('opus-mt-he-en'				,		dry_run=_UpperCamelCase   )
							assert mmeta["long_pair"] == "heb-eng"














def      lowercase__      (     __snake_case    :							int     ,       __snake_case    :							int  ):


					'''simple docstring'''


					if a < 0 or b < 0:
										raise ValueError('the value of both inputs must be positive'  )

					UpperCAmelCase_    :      Tuple            =						str(bin(__snake_case  )  )[2:]  # remove the leading "0b"
					UpperCAmelCase_    :      Union[str, Any]            =						str(bin(__snake_case  )  )[2:]  # remove the leading "0b"

					UpperCAmelCase_    :      List[Any]            =						max(len(__snake_case  )     ,       len(__snake_case  )  )

					return "0b" + "".join(
					    str(int(char_a == '1' and char_b == '1'  )  )
					    for char_a, char_b in zip(a_binary.zfill(__snake_case  )     ,       b_binary.zfill(__snake_case  )  )  )


if __name__ == "__main__":
		import doctest

		doctest.testmod()






