


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 	__lowercase					(	datasets.Metric	):





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






         """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 							_lowercase					(		self    :       Tuple       ,							__lowerCamelCase    :       List[Any]							)     -> Union[str, 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      					=  """bleurt-base-128"""

         if self.config_name.lower() in CHECKPOINT_URLS:
            UpperCAmelCase      					=  self.config_name.lower()

         elif self.config_name.upper() in CHECKPOINT_URLS:
            UpperCAmelCase      					=  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      					=  dl_manager.download_and_extract(CHECKPOINT_URLS[checkpoint_name]							)
         UpperCAmelCase      					=  score.BleurtScorer(os.path.join(__lowerCamelCase       ,							__lowerCamelCase							)							)





      def 							_lowercase					(		self    :       Optional[Any]       ,							__lowerCamelCase    :       Any       ,							__lowerCamelCase    :       int							)     -> Dict:






         """simple docstring"""







         UpperCAmelCase      					=  self.scorer.score(references=__lowerCamelCase       ,							candidates=__lowerCamelCase							)
         return {"scores": scores}







from __future__ import annotations

import math
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->bool:

   if 1 < number < 4:
      # 2 and 3 are primes
      return True
   elif number < 2 or number % 2 == 0 or number % 3 == 0:
      # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
      return False

   # All primes number are in format of 6k +/- 1
   for i in range(5	,    int(math.sqrt(lowerCAmelCase_ ) + 1 )	,    6 ):
      if number % i == 0 or number % (i + 2) == 0:
         return False
   return True


__a	 =      [num for num in range(3, 10_0001, 2) if not is_prime(num)]
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->list[int]:
   if not isinstance(lowerCAmelCase_	,    lowerCAmelCase_ ):
      raise ValueError("""n must be an integer""" )
   if n <= 0:
      raise ValueError("""n must be >= 0""" )

   UpperCAmelCase      					=  []
   for num in range(len(lowerCAmelCase_ ) ):
      UpperCAmelCase      					=  0
      while 2 * i * i <= odd_composites[num]:
         UpperCAmelCase      					=  odd_composites[num] - 2 * i * i
         if is_prime(lowerCAmelCase_ ):
            break
         i += 1
      else:
         list_nums.append(odd_composites[num] )
         if len(lowerCAmelCase_ ) == n:
            return list_nums

   return []
def 	_UpperCamelCase					(    )    ->int:
   return compute_nums(1 )[0]


if __name__ == "__main__":
 print(F"""{solution() = }""")



