import os

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

import datasets


_lowerCAmelCase       =		datasets.logging.get_logger(__name__)


_lowerCAmelCase       =		"\\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"

_lowerCAmelCase       =		"\\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"

_lowerCAmelCase       =		"\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"

_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  UpperCamelCase_						(   self      :     Any		):
												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      :     List[Any] ,			_A      :     int		):
												# 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\').'''		)
																	_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(_A ,			_A		)		)







							def  UpperCamelCase_						(   self      :     Dict ,			_A      :     List[str] ,			_A      :     Dict		):
												_UpperCamelCase			     =     self.scorer.score(references=_A ,			candidates=_A		)
												return {"scores": scores}




from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase		   =			logging.get_logger(__name__)

lowerCamelCase		   =			{
    'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}




class A    (  UpperCamelCase_	):
      UpperCamelCase__				:    Union[str, Any] ='vit_msn'






      def __init__(   self		:	Union[str, Any]     ,  lowercase_		:	List[str]=768     ,  lowercase_		:	Optional[int]=12     ,  lowercase_		:	List[str]=12     ,  lowercase_		:	List[Any]=3072     ,  lowercase_		:	int="gelu"     ,  lowercase_		:	List[Any]=0.0     ,  lowercase_		:	Optional[int]=0.0     ,  lowercase_		:	Dict=0.02     ,  lowercase_		:	Any=1E-06     ,  lowercase_		:	Union[str, Any]=224     ,  lowercase_		:	Optional[int]=16     ,  lowercase_		:	List[Any]=3     ,  lowercase_		:	Any=True     ,  **lowercase_		:	Tuple     ,  )   ->		Dict:
             """simple docstring"""




             super().__init__(**lowercase_					)

             _lowerCamelCase			:						Dict            =hidden_size
             _lowerCamelCase			:						Any            =num_hidden_layers
             _lowerCamelCase			:						Union[str, Any]            =num_attention_heads
             _lowerCamelCase			:						List[Any]            =intermediate_size
             _lowerCamelCase			:						Tuple            =hidden_act
             _lowerCamelCase			:						Any            =hidden_dropout_prob
             _lowerCamelCase			:						Dict            =attention_probs_dropout_prob
             _lowerCamelCase			:						Any            =initializer_range
             _lowerCamelCase			:						List[Any]            =layer_norm_eps
             _lowerCamelCase			:						Optional[int]            =image_size
             _lowerCamelCase			:						Optional[int]            =patch_size
             _lowerCamelCase			:						List[Any]            =num_channels
             _lowerCamelCase			:						Optional[Any]            =qkv_bias


