



"""simple docstring"""
import datasets


SCREAMING_SNAKE_CASE_				= '\\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'

SCREAMING_SNAKE_CASE_				= '\\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'

SCREAMING_SNAKE_CASE_				= '\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        lowerCAmelCase_						(							SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)			->      Tuple:
							return (preds == labels).mean()




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






							def snake_case_  (   self      ):
														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 snake_case_  (   self			,     a_			,     a_      ):
														return {"accuracy": simple_accuracy(UpperCAmelCase_			,     UpperCAmelCase_      )}




"""simple docstring"""
def        lowerCAmelCase_						(							SCREAMING_SNAKE_CASE__ = 10, SCREAMING_SNAKE_CASE__ = 1_000, SCREAMING_SNAKE_CASE__ = True	)			->      int:
		assert (
		    isinstance(SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)
		    and isinstance(SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)
		    and isinstance(SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)
		), "Invalid type of value(s) specified to function!"

		if min_val > max_val:
				raise ValueError("Invalid value for min_val or max_val (min_value < max_value)"	)
		return min_val if option else max_val



def        lowerCAmelCase_						(							SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)			->      int:
		return int((number_a + number_a) / 2	)



def        lowerCAmelCase_						(							SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)			->      None:
		assert (
		    isinstance(SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	) and isinstance(SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	) and isinstance(SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)
		), 'argument values must be type of "int"'

		if lower > higher:
				raise ValueError("argument value for lower and higher must be(lower > higher)"	)

		if not lower < to_guess < higher:
				raise ValueError(
				    "guess value must be within the range of lower and higher value"	)

		def answer(SCREAMING_SNAKE_CASE__	) -> str:
				if number > to_guess:
						return "high"
				elif number < to_guess:
						return "low"
				else:
						return "same"

		print("started..."	)

		a_     :      List[str] 						=     lower
		a_     :      Dict 						=     higher

		a_     :      str 						=     []

		while True:
				a_     :      List[str] 						=     get_avg(SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)
				last_numbers.append(SCREAMING_SNAKE_CASE__	)

				if answer(SCREAMING_SNAKE_CASE__	) == "low":
						a_     :      Optional[Any] 						=     number
				elif answer(SCREAMING_SNAKE_CASE__	) == "high":
						a_     :      Union[str, Any] 						=     number
				else:
						break

		print(F"""guess the number : {last_numbers[-1]}"""	)
		print(F"""details : {last_numbers!s}"""	)



def        lowerCAmelCase_						(							)			->      None:
		a_     :      str 						=     int(input("Enter lower value : "	).strip()	)
		a_     :      Dict 						=     int(input("Enter high value : "	).strip()	)
		a_     :      Optional[Any] 						=     int(input("Enter value to guess : "	).strip()	)
		guess_the_number(SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)


if __name__ == "__main__":
					main()