



import os

from bleurt import score  # From: git+https://github.com/google-research/bleurt.git

import datasets


__A   			=datasets.logging.get_logger(__name__)


__A   			='''\
@inproceedings{bleurt,
  title={BLEURT: Learning Robust Metrics for Text Generation},
  author={Thibault Sellam and Dipanjan Das and Ankur P. Parikh},
  booktitle={ACL},
  year={2020},
  url={https://arxiv.org/abs/2004.04696}
}
'''

__A   			='''\
BLEURT a learnt evaluation metric for Natural Language Generation. It is built using multiple phases of transfer learning starting from a pretrained BERT model (Devlin et al. 2018)
and then employing another pre-training phrase using synthetic data. Finally it is trained on WMT human annotations. You may run BLEURT out-of-the-box or fine-tune
it for your specific application (the latter is expected to perform better).

See the project\'s README at https://github.com/google-research/bleurt#readme for more information.
'''

__A   			='''
BLEURT score.

Args:
    `predictions` (list of str): prediction/candidate sentences
    `references` (list of str): reference sentences
    `checkpoint` BLEURT checkpoint. Will default to BLEURT-tiny if None.

Returns:
    \'scores\': List of scores.
Examples:

    >>> predictions = ["hello there", "general kenobi"]
    >>> references = ["hello there", "general kenobi"]
    >>> bleurt = datasets.load_metric("bleurt")
    >>> results = bleurt.compute(predictions=predictions, references=references)
    >>> print([round(v, 2) for v in results["scores"]])
    [1.03, 1.04]
'''

__A   			={
    '''bleurt-tiny-128''': '''https://storage.googleapis.com/bleurt-oss/bleurt-tiny-128.zip''',
    '''bleurt-tiny-512''': '''https://storage.googleapis.com/bleurt-oss/bleurt-tiny-512.zip''',
    '''bleurt-base-128''': '''https://storage.googleapis.com/bleurt-oss/bleurt-base-128.zip''',
    '''bleurt-base-512''': '''https://storage.googleapis.com/bleurt-oss/bleurt-base-512.zip''',
    '''bleurt-large-128''': '''https://storage.googleapis.com/bleurt-oss/bleurt-large-128.zip''',
    '''bleurt-large-512''': '''https://storage.googleapis.com/bleurt-oss/bleurt-large-512.zip''',
    '''BLEURT-20-D3''': '''https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D3.zip''',
    '''BLEURT-20-D6''': '''https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D6.zip''',
    '''BLEURT-20-D12''': '''https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D12.zip''',
    '''BLEURT-20''': '''https://storage.googleapis.com/bleurt-oss-21/BLEURT-20.zip''',
}

@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION						,_KWARGS_DESCRIPTION   )
class 		UpperCAmelCase__			(			datasets.Metric   ):




			'''simple docstring'''






			def  snake_case__     (   self							: Any ):
					'''simple docstring'''





					return datasets.MetricInfo(
					    description=_DESCRIPTION       ,       citation=_CITATION       ,       homepage='''https://github.com/google-research/bleurt'''       ,       inputs_description=_KWARGS_DESCRIPTION       ,       features=datasets.Features(
					        {
					            '''predictions''': datasets.Value('''string'''       ,       id='''sequence''' ),
					            '''references''': datasets.Value('''string'''       ,       id='''sequence''' ),
					        } )       ,       codebase_urls=['''https://github.com/google-research/bleurt''']       ,       reference_urls=['''https://github.com/google-research/bleurt''', '''https://arxiv.org/abs/2004.04696''']       ,       )




			def  snake_case__     (   self							: str       ,       a_							: Any ):
					'''simple docstring'''





					if self.config_name == "default":
							logger.warning(
							    '''Using default BLEURT-Base checkpoint for sequence maximum length 128. '''
							    '''You can use a bigger model for better results with e.g.: datasets.load_metric(\'bleurt\', \'bleurt-large-512\').''' )
							__UpperCAmelCase    :     str													=	"bleurt-base-128"

					if self.config_name.lower() in CHECKPOINT_URLS:
							__UpperCAmelCase    :     Union[str, Any]													=	self.config_name.lower()

					elif self.config_name.upper() in CHECKPOINT_URLS:
							__UpperCAmelCase    :     List[Any]													=	self.config_name.upper()

					else:
							raise KeyError(
							    F'{self.config_name} model not found. You should supply the name of a model checkpoint for bleurt in {CHECKPOINT_URLS.keys()}' )

					# download the model checkpoint specified by self.config_name and set up the scorer
					__UpperCAmelCase    :     Union[str, Any]													=	dl_manager.download_and_extract(CHECKPOINT_URLS[checkpoint_name] )
					__UpperCAmelCase    :     List[str]													=	score.BleurtScorer(os.path.join(_A       ,       _A ) )




			def  snake_case__     (   self							: str       ,       a_							: List[Any]       ,       a_							: Optional[int] ):
					'''simple docstring'''





					__UpperCAmelCase    :     Tuple													=	self.scorer.score(references=_A       ,       candidates=_A )
					return {"scores": scores}






def       _snake_case	(   lowerCAmelCase							:   int   , lowerCAmelCase							:   int	):
		"""simple docstring"""







		while b:
				SCREAMING_SNAKE_CASE_      ,    SCREAMING_SNAKE_CASE_  :		int				      =    b, a % b
		return a




def       _snake_case	(   lowerCAmelCase							:   int   , lowerCAmelCase							:   int	):
		"""simple docstring"""







		return a if b == 0 else euclidean_gcd_recursive(lowerCAmelCase   , a % b	)




def       _snake_case	(   ):
		"""simple docstring"""







		print(f'euclidean_gcd(3, 5) = {euclidean_gcd(3   , 5	)}'	)
		print(f'euclidean_gcd(5, 3) = {euclidean_gcd(5   , 3	)}'	)
		print(f'euclidean_gcd(1, 3) = {euclidean_gcd(1   , 3	)}'	)
		print(f'euclidean_gcd(3, 6) = {euclidean_gcd(3   , 6	)}'	)
		print(f'euclidean_gcd(6, 3) = {euclidean_gcd(6   , 3	)}'	)

		print(f'euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3   , 5	)}'	)
		print(f'euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5   , 3	)}'	)
		print(f'euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1   , 3	)}'	)
		print(f'euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3   , 6	)}'	)
		print(f'euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6   , 3	)}'	)


if __name__ == "__main__":
		main()
