import os

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

import datasets


__lowerCamelCase					:	str       =  datasets.logging.get_logger(__name__)


__lowerCamelCase					:	str       =  '''\
@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					:	Union[str, Any]       =  '''\
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					:	List[str]       =  '''
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					:	str       =  {
    '''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 		a__						(					datasets.Metric					):

					def 				__UpperCamelCase   (    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 				__UpperCamelCase   (    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')."    )
									SCREAMING_SNAKE_CASE_  :		str				      =    "bleurt-base-128"

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

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






					def 				__UpperCamelCase   (    self      :       str,_A      :       List[Any],_A      :       Optional[int]    ):







							"""simple docstring"""






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




"""simple docstring"""







import pytest

from datasets import inspect_metric, list_metrics, load_metric


@pytest.fixture
def      lowercase			(				A_       )->      List[Any]:
  '''simple docstring'''







  monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings"  ,   set()       )


@pytest.fixture
def      lowercase			(				A_       )->      Tuple:
  '''simple docstring'''







  class 						_A  :







      """simple docstring"""




      def __init__(					self				:    str				, __UpperCAmelCase				:    int):
        a						:		List[Any]      							=			metric_id






  class 						_A  :







      """simple docstring"""




      UpperCAmelCase       :							Union[str, Any]	=       [MetricMock(_a  ) for metric_id in ["""accuracy""", """mse""", """precision""", """codeparrot/apps_metric"""]]






      def 	__snake_case							(					self				:    List[str]):
        return self._metrics






  monkeypatch.setattr("datasets.inspect.huggingface_hub"  ,   HfhMock()       )







@pytest.mark.parametrize(
    "func, args"  ,   [(load_metric, ("metrics/mse",)), (list_metrics, ()), (inspect_metric, ("metrics/mse", "tmp_path"))]       )
def      lowercase			(				A_  ,   A_  ,   A_  ,   A_  ,   A_       )->      Any:
  '''simple docstring'''







  if "tmp_path" in args:
    a						:		Union[str, Any]      							=			tuple(arg if arg != "tmp_path" else tmp_path for arg in args       )
  with pytest.warns(A_  ,   match="https://huggingface.co/docs/evaluate"       ):
    func(*A_       )






