


'''simple docstring'''

import datasets


lowerCamelCase							:   str  						=	'\\n@InProceedings{conneau2018xnli,\n  author = "Conneau, Alexis\n                 and Rinott, Ruty\n                 and Lample, Guillaume\n                 and Williams, Adina\n                 and Bowman, Samuel R.\n                 and Schwenk, Holger\n                 and Stoyanov, Veselin",\n  title = "XNLI: Evaluating Cross-lingual Sentence Representations",\n  booktitle = "Proceedings of the 2018 Conference on Empirical Methods\n               in Natural Language Processing",\n  year = "2018",\n  publisher = "Association for Computational Linguistics",\n  location = "Brussels, Belgium",\n}\n'

lowerCamelCase							:   Any  						=	'\\nXNLI is a subset of a few thousand examples from MNLI which has been translated\ninto a 14 different languages (some low-ish resource). As with MNLI, the goal is\nto predict textual entailment (does sentence A imply/contradict/neither sentence\nB) and is a classification task (given two sentences, predict one of three\nlabels).\n'

lowerCamelCase							:   List[str]  						=	'\nComputes XNLI score which is just simple accuracy.\nArgs:\n    predictions: Predicted labels.\n    references: Ground truth labels.\nReturns:\n    \'accuracy\': accuracy\nExamples:\n\n    >>> predictions = [0, 1]\n    >>> references = [0, 1]\n    >>> xnli_metric = datasets.load_metric("xnli")\n    >>> results = xnli_metric.compute(predictions=predictions, references=references)\n    >>> print(results)\n    {\'accuracy\': 1.0}\n'

def _SCREAMING_SNAKE_CASE      (A  , A       )       ->       Optional[Any]:






       """simple docstring"""







       return (preds == labels).mean()

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





      '''simple docstring'''






      def       UpperCamelCase__		(self    :    List[str] ):

             '''simple docstring'''







             return datasets.MetricInfo(
                 description=_DESCRIPTION   ,						citation=_CITATION   ,						inputs_description=_KWARGS_DESCRIPTION   ,						features=datasets.Features(
                     {
                         '''predictions''': datasets.Value('''int64''' if self.config_name != '''sts-b''' else '''float32''' ),
                         '''references''': datasets.Value('''int64''' if self.config_name != '''sts-b''' else '''float32''' ),
                     } )   ,						codebase_urls=[]   ,						reference_urls=[]   ,						format='''numpy'''   ,						)






      def       UpperCamelCase__		(self    :    str   ,						UpperCamelCase    :    Optional[int]   ,						UpperCamelCase    :    List[str] ):

             '''simple docstring'''







             return {"accuracy": simple_accuracy(UpperCamelCase   ,						UpperCamelCase )}








'''simple docstring'''

import unittest

from transformers import DonutProcessor


lowerCamelCase							:   Tuple  						=	'naver-clova-ix/donut-base'
class   __lowerCAmelCase						(unittest.TestCase     ):





      '''simple docstring'''






      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= DonutProcessor.from_pretrained(UpperCamelCase )






      def       UpperCamelCase__		(self    :    Tuple ):

             '''simple docstring'''







             lowercase__      			= {
                 '''name''': '''John Doe''',
                 '''age''': '''99''',
                 '''city''': '''Atlanta''',
                 '''state''': '''GA''',
                 '''zip''': '''30301''',
                 '''phone''': '''123-4567''',
                 '''nicknames''': [{'''nickname''': '''Johnny'''}, {'''nickname''': '''JD'''}],
             }

             lowercase__      			= (
                 '''<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>'''
                 '''<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>'''
                 '''<s_nicknames><s_nickname>Johnny</s_nickname>'''
                 '''<sep/><s_nickname>JD</s_nickname></s_nicknames>'''
             )
             lowercase__      			= self.processor.tokenajson(UpperCamelCase )

             self.assertDictEqual(UpperCamelCase   ,						UpperCamelCase )




