


"""simple docstring"""




import unittest

from diffusers import __version__
from diffusers.utils import deprecate




class A  (       unittest.TestCase					):
      UpperCamelCase__							:  int				='.'.join([str(int(__version__.split('.'					)[0]					) + 1					)] + __version__.split('.'					)[1:]					)
      UpperCamelCase__							:  Optional[Any]				='0.0.1'






      def 	lowerCamelCase	( self						:					Union[str, Any]			) ->						Any:
             """simple docstring"""




             _lowerCamelCase	:		Optional[Any]          ={"deprecated_arg": 4}

             with self.assertWarns(__lowerCamelCase			) as warning:
                    _lowerCamelCase	:		Optional[Any]          =deprecate('deprecated_arg'      ,       self.higher_version      ,       'message'      ,       take_from=__lowerCamelCase			)

             assert output == 4
             assert (
                 str(warning.warning			)
                 == F'''The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}.'''
                 " message"
             )






      def 	lowerCamelCase	( self						:					List[str]			) ->						str:
             """simple docstring"""




             _lowerCamelCase	:		List[str]          ={"deprecated_arg": 4}

             with self.assertWarns(__lowerCamelCase			) as warning:
                    _lowerCamelCase	:		Dict          =deprecate(('deprecated_arg', self.higher_version, 'message')      ,       take_from=__lowerCamelCase			)

             assert output == 4
             assert (
                 str(warning.warning			)
                 == F'''The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}.'''
                 " message"
             )






      def 	lowerCamelCase	( self						:					Optional[Any]			) ->						Optional[int]:
             """simple docstring"""




             _lowerCamelCase	:		List[str]          ={"deprecated_arg_1": 4, "deprecated_arg_2": 8}
             with self.assertWarns(__lowerCamelCase			) as warning:
                    _lowerCamelCase	:		Any          =deprecate(
                        ('deprecated_arg_1', self.higher_version, 'Hey')      ,       ('deprecated_arg_2', self.higher_version, 'Hey')      ,       take_from=__lowerCamelCase      ,       )
             assert output_a == 4
             assert output_a == 8
             assert (
                 str(warning.warnings[0].message			)
                 == "The `deprecated_arg_1` argument is deprecated and will be removed in version"
                 F''' {self.higher_version}. Hey'''
             )
             assert (
                 str(warning.warnings[1].message			)
                 == "The `deprecated_arg_2` argument is deprecated and will be removed in version"
                 F''' {self.higher_version}. Hey'''
             )






      def 	lowerCamelCase	( self						:					Dict			) ->						Optional[int]:
             """simple docstring"""




             _lowerCamelCase	:		Any          ={"deprecated_arg": 4}

             with self.assertRaises(__lowerCamelCase			) as error:
                    deprecate(('wrong_arg', self.higher_version, 'message')      ,       take_from=__lowerCamelCase			)

             assert "test_deprecate_function_incorrect_arg in" in str(error.exception			)
             assert "line" in str(error.exception			)
             assert "got an unexpected keyword argument `deprecated_arg`" in str(error.exception			)






      def 	lowerCamelCase	( self						:					Optional[Any]			) ->						Union[str, Any]:
             """simple docstring"""




             with self.assertWarns(__lowerCamelCase			) as warning:
                    deprecate(('deprecated_arg', self.higher_version, 'message')			)

             assert (
                 str(warning.warning			)
                 == F'''`deprecated_arg` is deprecated and will be removed in version {self.higher_version}. message'''
             )






      def 	lowerCamelCase	( self						:					Union[str, Any]			) ->						List[str]:
             """simple docstring"""




             with self.assertWarns(__lowerCamelCase			) as warning:
                    deprecate(
                        ('deprecated_arg_1', self.higher_version, 'Hey')      ,       ('deprecated_arg_2', self.higher_version, 'Hey')      ,       )
             assert (
                 str(warning.warnings[0].message			)
                 == F'''`deprecated_arg_1` is deprecated and will be removed in version {self.higher_version}. Hey'''
             )
             assert (
                 str(warning.warnings[1].message			)
                 == F'''`deprecated_arg_2` is deprecated and will be removed in version {self.higher_version}. Hey'''
             )






      def 	lowerCamelCase	( self						:					Tuple			) ->						Any:
             """simple docstring"""




             class A  :
                   UpperCamelCase__							:  int				=5

             with self.assertWarns(__lowerCamelCase			) as warning:
                    _lowerCamelCase	:		str          =deprecate(('arg', self.higher_version, 'message')      ,       take_from=Args()			)

             assert arg == 5
             assert (
                 str(warning.warning			)
                 == F'''The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'''
             )






      def 	lowerCamelCase	( self						:					List[str]			) ->						Union[str, Any]:
             """simple docstring"""




             class A  :
                   UpperCamelCase__							:  List[str]				=5
                   UpperCamelCase__							:  List[str]				=7

             with self.assertWarns(__lowerCamelCase			) as warning:
                    _lowerCamelCase	:		Tuple          =deprecate(
                        ('arg', self.higher_version, 'message')      ,       ('foo', self.higher_version, 'message')      ,       ('does not exist', self.higher_version, 'message')      ,       take_from=Args()      ,       )

             assert arg_a == 5
             assert arg_a == 7
             assert (
                 str(warning.warning			)
                 == F'''The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'''
             )
             assert (
                 str(warning.warnings[0].message			)
                 == F'''The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'''
             )
             assert (
                 str(warning.warnings[1].message			)
                 == F'''The `foo` attribute is deprecated and will be removed in version {self.higher_version}. message'''
             )






      def 	lowerCamelCase	( self						:					Any			) ->						Tuple:
             """simple docstring"""




             _lowerCamelCase	:		List[Any]          ={"deprecated_arg": 4}

             with self.assertRaises(__lowerCamelCase			) as error:
                    deprecate(('wrong_arg', self.lower_version, 'message')      ,       take_from=__lowerCamelCase			)

             assert (
                 str(error.exception			)
                 == "The deprecation tuple ('wrong_arg', '0.0.1', 'message') should be removed since diffusers' version"
                 F''' {__version__} is >= {self.lower_version}'''
             )






      def 	lowerCamelCase	( self						:					Optional[Any]			) ->						Optional[Any]:
             """simple docstring"""




             with self.assertWarns(__lowerCamelCase			) as warning:
                    deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')      ,       standard_warn=__lowerCamelCase			)

             assert str(warning.warning			) == "This message is better!!!"






      def 	lowerCamelCase	( self						:					int			) ->						Union[str, Any]:
             """simple docstring"""




             with self.assertWarns(__lowerCamelCase			) as warning:
                    deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')      ,       standard_warn=__lowerCamelCase			)
             assert str(warning.warning			) == "This message is better!!!"
             assert "diffusers/tests/others/test_utils.py" in warning.filename






import torch
from transformers import AutoModelForSequenceClassification, AutoTokenizer, Trainer, TrainingArguments

import datasets


lowerCamelCase						 =	'\\n@article{eddine2021frugalscore,\n  title={FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metrics for Automatic Text Generation},\n  author={Eddine, Moussa Kamal and Shang, Guokan and Tixier, Antoine J-P and Vazirgiannis, Michalis},\n  journal={arXiv preprint arXiv:2110.08559},\n  year={2021}\n}\n'

lowerCamelCase						 =	'\\nFrugalScore is a reference-based metric for NLG models evaluation. It is based on a distillation approach that allows to learn a fixed, low cost version of any expensive NLG metric, while retaining most of its original performance.\n'


lowerCamelCase						 =	'\nCalculates how good are predictions given some references, using certain scores.\nArgs:\n    predictions (list of str): list of predictions to score. Each predictions\n        should be a string.\n    references (list of str): list of reference for each prediction. Each\n        reference should be a string.\n    batch_size (int): the batch size for predictions.\n    max_length (int): maximum sequence length.\n    device (str): either gpu or cpu\nReturns:\n    scores (list of int): list of scores.\nExamples:\n    >>> frugalscore = datasets.load_metric("frugalscore")\n    >>> results = frugalscore.compute(predictions=[\'hello there\', \'huggingface\'], references=[\'hello world\', \'hugging face\'])\n    >>> print([round(s, 3) for s in results["scores"]])\n    [0.631, 0.645]\n'




@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION   ,							_KWARGS_DESCRIPTION					)
class A  (       datasets.Metric					):






      def 	lowerCamelCase	( self						:					Tuple			) ->						Optional[Any]:
             """simple docstring"""




             return datasets.MetricInfo(
                 description=_DESCRIPTION      ,       citation=_CITATION      ,       inputs_description=_KWARGS_DESCRIPTION      ,       features=datasets.Features(
                     {
                         'predictions': datasets.Value('string'			),
                         'references': datasets.Value('string'			),
                     }			)      ,       homepage='https://github.com/moussaKam/FrugalScore'      ,       )






      def 	lowerCamelCase	( self						:					Optional[int]      ,       lowercase_						:					Union[str, Any]			) ->						int:
             """simple docstring"""




             if self.config_name == "default":
                    _lowerCamelCase	:		Optional[int]          ='moussaKam/frugalscore_tiny_bert-base_bert-score'
             else:
                    _lowerCamelCase	:		List[Any]          =self.config_name
             _lowerCamelCase	:		str          =AutoModelForSequenceClassification.from_pretrained(lowercase_			)
             _lowerCamelCase	:		str          =AutoTokenizer.from_pretrained(lowercase_			)






      def 	lowerCamelCase	( self						:					List[Any]      ,       lowercase_						:					List[str]      ,       lowercase_						:					str      ,       lowercase_						:					Optional[int]=32      ,       lowercase_						:					int=128      ,       lowercase_						:					Tuple=None      ,       ) ->						str:
             """simple docstring"""




             assert len(lowercase_			) == len(
                 lowercase_			), "predictions and references should have the same number of sentences."
             if device is not None:
                    assert device in ["gpu", "cpu"], "device should be either gpu or cpu."
             else:
                    _lowerCamelCase	:		List[str]          ='gpu' if torch.cuda.is_available() else 'cpu'
             _lowerCamelCase	:		List[str]          =TrainingArguments(
                 'trainer'      ,       fpaa=(device == 'gpu')      ,       per_device_eval_batch_size=lowercase_      ,       report_to='all'      ,       no_cuda=(device == 'cpu')      ,       log_level='warning'      ,       )
             _lowerCamelCase	:		str          ={'sentence1': predictions, 'sentence2': references}
             _lowerCamelCase	:		Tuple          =datasets.Dataset.from_dict(lowercase_			)

             def tokenize_function(lowercase_						:					Any			):
                    return self.tokenizer(
                        data['sentence1']      ,       data['sentence2']      ,       max_length=lowercase_      ,       truncation=lowercase_      ,       padding=lowercase_			)

             _lowerCamelCase	:		Dict          =raw_datasets.map(lowercase_      ,       batched=lowercase_			)
             tokenized_datasets.remove_columns(['sentence1', 'sentence2']			)
             _lowerCamelCase	:		Union[str, Any]          =Trainer(self.model      ,       lowercase_      ,       tokenizer=self.tokenizer			)
             _lowerCamelCase	:		List[str]          =trainer.predict(lowercase_			)
             return {"scores": list(predictions.predictions.squeeze(-1			)			)}


