




import datasets


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

__lowerCamelCase   :						Optional[Any]				=			'''\
XNLI is a subset of a few thousand examples from MNLI which has been translated
into a 14 different languages (some low-ish resource). As with MNLI, the goal is
to predict textual entailment (does sentence A imply/contradict/neither sentence
B) and is a classification task (given two sentences, predict one of three
labels).
'''

__lowerCamelCase   :						Optional[Any]				=			'''
Computes XNLI score which is just simple accuracy.
Args:
    predictions: Predicted labels.
    references: Ground truth labels.
Returns:
    \'accuracy\': accuracy
Examples:

    >>> predictions = [0, 1]
    >>> references = [0, 1]
    >>> xnli_metric = datasets.load_metric("xnli")
    >>> results = xnli_metric.compute(predictions=predictions, references=references)
    >>> print(results)
    {\'accuracy\': 1.0}
'''







def 		lowercase__   (		__A:	Optional[Any]							,__A:	int				):





     '''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			:   Optional[int]  )						->   Dict:
        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			:   int       ,						lowerCamelCase_			:   Any       ,						lowerCamelCase_			:   Tuple  )						->   Optional[Any]:
        return {"accuracy": simple_accuracy(lowerCamelCase_       ,						lowerCamelCase_  )}









import sys
import turtle







def 		lowercase__   (		__A:	tuple[float, float]							,__A:	tuple[float, float]				):





					'''simple docstring'''






					return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2







def 		lowercase__   (		__A:	tuple[float, float]							,__A:	tuple[float, float]							,__A:	tuple[float, float]							,__A:	int							,):





					'''simple docstring'''






					my_pen.up()
					my_pen.goto(vertexa[0]							,vertexa[1]				)
					my_pen.down()
					my_pen.goto(vertexa[0]							,vertexa[1]				)
					my_pen.goto(vertexa[0]							,vertexa[1]				)
					my_pen.goto(vertexa[0]							,vertexa[1]				)

					if depth == 0:
										return

					triangle(__A							,get_mid(__A							,__A				)							,get_mid(__A							,__A				)							,depth - 1				)
					triangle(__A							,get_mid(__A							,__A				)							,get_mid(__A							,__A				)							,depth - 1				)
					triangle(__A							,get_mid(__A							,__A				)							,get_mid(__A							,__A				)							,depth - 1				)


if __name__ == "__main__":
	if len(sys.argv) != 2:
		raise ValueError(
		    '''Correct format for using this script: '''
		    '''python fractals.py <int:depth_for_fractal>'''
		)
	__lowerCamelCase   :						Any				=			turtle.Turtle()
	my_pen.ht()
	my_pen.speed(5)
	my_pen.pencolor('''red''')

	__lowerCamelCase   :						Optional[Any]				=			[(-1_75, -1_25), (0, 1_75), (1_75, -1_25)]  # vertices of triangle
	triangle(vertices[0], vertices[1], vertices[2], int(sys.argv[1]))



