


import os

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

import datasets


A      :    Optional[Any]		=					datasets.logging.get_logger(__name__)


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

A      :    List[str]		=					"\\nBLEURT 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)\nand 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\nit for your specific application (the latter is expected to perform better).\n\nSee the project's README at https://github.com/google-research/bleurt#readme for more information.\n"

A      :    Optional[Any]		=					"\nBLEURT score.\n\nArgs:\n    `predictions` (list of str): prediction/candidate sentences\n    `references` (list of str): reference sentences\n    `checkpoint` BLEURT checkpoint. Will default to BLEURT-tiny if None.\n\nReturns:\n    'scores': List of scores.\nExamples:\n\n    >>> predictions = [\"hello there\", \"general kenobi\"]\n    >>> references = [\"hello there\", \"general kenobi\"]\n    >>> bleurt = datasets.load_metric(\"bleurt\")\n    >>> results = bleurt.compute(predictions=predictions, references=references)\n    >>> print([round(v, 2) for v in results[\"scores\"]])\n    [1.03, 1.04]\n"

A      :    int		=					{
    "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):


       """simple docstring"""




       def 						lowerCAmelCase     (   self							:			str       ):


             '''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							:			List[str]					,      __lowerCamelCase							:			List[str]       ):


             '''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')."       )
                   lowerCamelCase__		:				List[str]    =  "bleurt-base-128"

             if self.config_name.lower() in CHECKPOINT_URLS:
                   lowerCamelCase__		:				Any    =  self.config_name.lower()

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





       def 						lowerCAmelCase     (   self							:			List[str]					,      __lowerCamelCase							:			List[str]					,      __lowerCamelCase							:			str       ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[int]    =  self.scorer.score(references=__lowerCamelCase					,      candidates=__lowerCamelCase       )
             return {"scores": scores}






def       lowercase_		(		_A			:    int    ,					_A			:    int						):

      """simple docstring"""




      while a != 0:
            lowerCamelCase__    ,   lowerCamelCase__		:				Optional[Any]    =  b % a, a
      return b


def       lowercase_		(		_A			:    int    ,					_A			:    int						):

      """simple docstring"""




      if gcd(_A    ,					_A						) != 1:
            lowerCamelCase__		:				List[str]    =  F"mod inverse of {a!r} and {m!r} does not exist"
            raise ValueError(_A						)
      lowerCamelCase__    ,   lowerCamelCase__    ,   lowerCamelCase__		:				Tuple    =  1, 0, a
      lowerCamelCase__    ,   lowerCamelCase__    ,   lowerCamelCase__		:				Optional[int]    =  0, 1, m
      while va != 0:
            lowerCamelCase__		:				Tuple    =  ua // va
            lowerCamelCase__    ,   lowerCamelCase__    ,   lowerCamelCase__    ,   lowerCamelCase__    ,   lowerCamelCase__    ,   lowerCamelCase__		:				str    =  (ua - q * va), (ua - q * va), (ua - q * va), va, va, va
      return ua % m


