





import warnings

from ...utils import is_sklearn_available, requires_backends


if is_sklearn_available():
					from scipy.stats import pearsonr, spearmanr
					from sklearn.metrics import fa_score, matthews_corrcoef


snake_case_     :       Optional[int]						=  (
    "This metric will be removed from the library soon, metrics should be handled with the 🤗 Evaluate "
    "library. You can have a look at this example script for pointers: "
    "https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_glue.py"
)





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			Optional[int],			SCREAMING_SNAKE_CASE__      :			List[str]   ) ->	Dict:
						warnings.warn(lowerCamelCase_,			lowerCamelCase_   )
						requires_backends(lowerCamelCase_,			'''sklearn'''   )
						return (preds == labels).mean()





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			Optional[Any],			SCREAMING_SNAKE_CASE__      :			List[str]   ) ->	Any:
						warnings.warn(lowerCamelCase_,			lowerCamelCase_   )
						requires_backends(lowerCamelCase_,			'''sklearn'''   )
						UpperCAmelCase_			:      Any     						=  simple_accuracy(lowerCamelCase_,			lowerCamelCase_   )
						UpperCAmelCase_			:      Any     						=  fa_score(y_true=lowerCamelCase_,			y_pred=lowerCamelCase_   )
						return {
						    "acc": acc,
						    "f1": fa,
						    "acc_and_f1": (acc + fa) / 2,
						}





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			Optional[int],			SCREAMING_SNAKE_CASE__      :			Optional[Any]   ) ->	Tuple:
						warnings.warn(lowerCamelCase_,			lowerCamelCase_   )
						requires_backends(lowerCamelCase_,			'''sklearn'''   )
						UpperCAmelCase_			:      Optional[int]     						=  pearsonr(lowerCamelCase_,			lowerCamelCase_   )[0]
						UpperCAmelCase_			:      List[str]     						=  spearmanr(lowerCamelCase_,			lowerCamelCase_   )[0]
						return {
						    "pearson": pearson_corr,
						    "spearmanr": spearman_corr,
						    "corr": (pearson_corr + spearman_corr) / 2,
						}





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			Dict,			SCREAMING_SNAKE_CASE__      :			Any,			SCREAMING_SNAKE_CASE__      :			Optional[Any]   ) ->	List[Any]:
						warnings.warn(lowerCamelCase_,			lowerCamelCase_   )
						requires_backends(lowerCamelCase_,			'''sklearn'''   )
						assert len(lowerCamelCase_   ) == len(lowerCamelCase_   ), F"""Predictions and labels have mismatched lengths {len(lowerCamelCase_   )} and {len(lowerCamelCase_   )}"""
						if task_name == "cola":
												return {"mcc": matthews_corrcoef(lowerCamelCase_,			lowerCamelCase_   )}
						elif task_name == "sst-2":
												return {"acc": simple_accuracy(lowerCamelCase_,			lowerCamelCase_   )}
						elif task_name == "mrpc":
												return acc_and_fa(lowerCamelCase_,			lowerCamelCase_   )
						elif task_name == "sts-b":
												return pearson_and_spearman(lowerCamelCase_,			lowerCamelCase_   )
						elif task_name == "qqp":
												return acc_and_fa(lowerCamelCase_,			lowerCamelCase_   )
						elif task_name == "mnli":
												return {"mnli/acc": simple_accuracy(lowerCamelCase_,			lowerCamelCase_   )}
						elif task_name == "mnli-mm":
												return {"mnli-mm/acc": simple_accuracy(lowerCamelCase_,			lowerCamelCase_   )}
						elif task_name == "qnli":
												return {"acc": simple_accuracy(lowerCamelCase_,			lowerCamelCase_   )}
						elif task_name == "rte":
												return {"acc": simple_accuracy(lowerCamelCase_,			lowerCamelCase_   )}
						elif task_name == "wnli":
												return {"acc": simple_accuracy(lowerCamelCase_,			lowerCamelCase_   )}
						elif task_name == "hans":
												return {"acc": simple_accuracy(lowerCamelCase_,			lowerCamelCase_   )}
						else:
												raise KeyError(lowerCamelCase_   )





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			List[str],			SCREAMING_SNAKE_CASE__      :			str,			SCREAMING_SNAKE_CASE__      :			Tuple   ) ->	Tuple:
						warnings.warn(lowerCamelCase_,			lowerCamelCase_   )
						requires_backends(lowerCamelCase_,			'''sklearn'''   )
						if len(lowerCamelCase_   ) != len(lowerCamelCase_   ):
												raise ValueError(F"""Predictions and labels have mismatched lengths {len(lowerCamelCase_   )} and {len(lowerCamelCase_   )}"""   )
						if task_name == "xnli":
												return {"acc": simple_accuracy(lowerCamelCase_,			lowerCamelCase_   )}
						else:
												raise KeyError(lowerCamelCase_   )












'''simple docstring'''







import sys
import turtle





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			tuple[float, float],			SCREAMING_SNAKE_CASE__      :			tuple[float, float]   ) ->	tuple[float, float]:
						return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2





def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			tuple[float, float],			SCREAMING_SNAKE_CASE__      :			tuple[float, float],			SCREAMING_SNAKE_CASE__      :			tuple[float, float],			SCREAMING_SNAKE_CASE__      :			int,			) ->	None:
						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(SCREAMING_SNAKE_CASE__,			get_mid(SCREAMING_SNAKE_CASE__,			SCREAMING_SNAKE_CASE__   ),			get_mid(SCREAMING_SNAKE_CASE__,			SCREAMING_SNAKE_CASE__   ),			depth - 1   )
						triangle(SCREAMING_SNAKE_CASE__,			get_mid(SCREAMING_SNAKE_CASE__,			SCREAMING_SNAKE_CASE__   ),			get_mid(SCREAMING_SNAKE_CASE__,			SCREAMING_SNAKE_CASE__   ),			depth - 1   )
						triangle(SCREAMING_SNAKE_CASE__,			get_mid(SCREAMING_SNAKE_CASE__,			SCREAMING_SNAKE_CASE__   ),			get_mid(SCREAMING_SNAKE_CASE__,			SCREAMING_SNAKE_CASE__   ),			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>"
										)
					snake_case_     :       Any						=  turtle.Turtle()
					my_pen.ht()
					my_pen.speed(5)
					my_pen.pencolor("red")

					snake_case_     :       Tuple						=  [(-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]))





