



'''simple docstring'''





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					):
  '''simple docstring'''




  def 							UpperCAmelCase_     (   self				)   ->		Optional[int]:
      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  ,__UpperCAmelCase				)   ->		List[str]:
      # check that config name specifies a valid BLEURT model
      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__			:  Dict											= """bleurt-base-128"""

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

      elif self.config_name.upper() in CHECKPOINT_URLS:
          lowerCAmelCase__			:  List[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__			:  List[Any]											= dl_manager.download_and_extract(CHECKPOINT_URLS[checkpoint_name]				)
      lowerCAmelCase__			:  Dict											= score.BleurtScorer(os.path.join(__UpperCAmelCase  ,__UpperCAmelCase				)				)






  def 							UpperCAmelCase_     (   self  ,__UpperCAmelCase  ,__UpperCAmelCase				)   ->		Optional[Any]:
      lowerCAmelCase__			:  Optional[Any]											= self.scorer.score(references=__UpperCAmelCase  ,candidates=__UpperCAmelCase				)
      return {"scores": scores}







'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCAmelCase										=     {
    '''configuration_blip_2''': [
        '''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Blip2Config''',
        '''Blip2QFormerConfig''',
        '''Blip2VisionConfig''',
    ],
    '''processing_blip_2''': ['''Blip2Processor'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase										=     [
     '''BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''Blip2Model''',
     '''Blip2QFormerModel''',
     '''Blip2PreTrainedModel''',
     '''Blip2ForConditionalGeneration''',
     '''Blip2VisionModel''',
 ]

if TYPE_CHECKING:
 from .configuration_blip_a import (
     BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP,
     BlipaConfig,
     BlipaQFormerConfig,
     BlipaVisionConfig,
 )
 from .processing_blip_a import BlipaProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_blip_a import (
      BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST,
      BlipaForConditionalGeneration,
      BlipaModel,
      BlipaPreTrainedModel,
      BlipaQFormerModel,
      BlipaVisionModel,
  )

else:
 import sys

 _lowerCAmelCase										=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


