
'''simple docstring'''





import os
from collections.abc import Iterator





def 				snake_case							(						UpperCAmelCase = "."		)->	Iterator[str]:







      """simple docstring"""


      for dir_path, dir_names, filenames in os.walk(_UpperCamelCase		):
            __A						=	[d for d in dir_names if d != '''scripts''' and d[0] not in '''._''']
            for filename in filenames:
                  if filename == "__init__.py":
                        continue
                  if os.path.splitext(_UpperCamelCase		)[1] in (".py", ".ipynb"):
                        yield os.path.join(_UpperCamelCase					,     _UpperCamelCase		).lstrip('./'		)





def 				snake_case							(						UpperCAmelCase		)->	List[str]:







      """simple docstring"""
      return f'{i * "  "}*' if i else "\n##"





def 				snake_case							(						UpperCAmelCase					,     UpperCAmelCase		)->	str:







      """simple docstring"""
      __A						=	old_path.split(os.sep		)
      for i, new_part in enumerate(new_path.split(os.sep		)		):
            if (i + 1 > len(_UpperCamelCase		) or old_parts[i] != new_part) and new_part:
                  print(f'{md_prefix(_UpperCamelCase		)} {new_part.replace("_"					,     " "		).title()}'		)
      return new_path





def 				snake_case							(						UpperCAmelCase = "."		)->	None:







      """simple docstring"""
      __A						=	''''''
      for filepath in sorted(good_file_paths(_UpperCamelCase		)		):
            __A						=	os.path.split(_UpperCamelCase		)
            if filepath != old_path:
                  __A						=	print_path(_UpperCamelCase					,     _UpperCamelCase		)
            __A						=	(filepath.count(os.sep		) + 1) if filepath else 0
            __A						=	f'{filepath}/{filename}'.replace(' '					,     '%20'		)
            __A						=	os.path.splitext(filename.replace('_'					,     ' '		).title()		)[0]
            print(f'{md_prefix(_UpperCamelCase		)} [{filename}]({url})'		)


if __name__ == "__main__":
 print_directory_md(".")













import os

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

import datasets


lowerCAmelCase_    =				datasets.logging.get_logger(__name__)


lowerCAmelCase_    =				'''\
@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}
}
'''

lowerCAmelCase_    =				'''\
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.
'''

lowerCAmelCase_    =				'''
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]
'''

lowerCAmelCase_    =				{
    '''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 					__lowerCAmelCase       (			datasets.Metric     ):






			def 			lowerCamelCase  (self    )     ->   Optional[int]:


							'''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 			lowerCamelCase  (self					,							__magic_name__    )     ->   List[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\').'''    )
											snake_case_						:    Dict				=  '''bleurt-base-128'''

							if self.config_name.lower() in CHECKPOINT_URLS:
											snake_case_						:    Optional[int]				=  self.config_name.lower()

							elif self.config_name.upper() in CHECKPOINT_URLS:
											snake_case_						:    Union[str, 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
							snake_case_						:    Any				=  dl_manager.download_and_extract(CHECKPOINT_URLS[checkpoint_name]    )
							snake_case_						:    Dict				=  score.BleurtScorer(os.path.join(__magic_name__					,							__magic_name__    )    )






			def 			lowerCamelCase  (self					,							__magic_name__					,							__magic_name__    )     ->   Union[str, Any]:


							'''simple docstring'''



							snake_case_						:    Dict				=  self.scorer.score(references=__magic_name__					,							candidates=__magic_name__    )
							return {"scores": scores}
