





"""simple docstring"""





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


lowerCAmelCase__     			=			(
    '''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       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		warnings.warn(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )
		requires_backends(_SCREAMING_SNAKE_CASE  ,	"sklearn"    )
		return (preds == labels).mean()


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		warnings.warn(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )
		requires_backends(_SCREAMING_SNAKE_CASE  ,	"sklearn"    )
		UpperCamelCase   =	simple_accuracy(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )
		UpperCamelCase   =	fa_score(y_true=_SCREAMING_SNAKE_CASE  ,	y_pred=_SCREAMING_SNAKE_CASE    )
		return {
		    "acc": acc,
		    "f1": fa,
		    "acc_and_f1": (acc + fa) / 2,
		}


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		warnings.warn(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )
		requires_backends(_SCREAMING_SNAKE_CASE  ,	"sklearn"    )
		UpperCamelCase   =	pearsonr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )[0]
		UpperCamelCase   =	spearmanr(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )[0]
		return {
		    "pearson": pearson_corr,
		    "spearmanr": spearman_corr,
		    "corr": (pearson_corr + spearman_corr) / 2,
		}


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


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






def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		warnings.warn(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )
		requires_backends(_SCREAMING_SNAKE_CASE  ,	"sklearn"    )
		if len(_SCREAMING_SNAKE_CASE    ) != len(_SCREAMING_SNAKE_CASE    ):
				raise ValueError(F"Predictions and labels have mismatched lengths {len(_SCREAMING_SNAKE_CASE    )} and {len(_SCREAMING_SNAKE_CASE    )}"    )
		if task_name == "xnli":
				return {"acc": simple_accuracy(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )}
		else:
				raise KeyError(_SCREAMING_SNAKE_CASE    )













"""simple docstring"""





import argparse
from collections import defaultdict


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	F"{file}_{class_name}_{test_name}"
		done_test[_id] += 1

		with open(_SCREAMING_SNAKE_CASE  ,	"r"    ) as f:
				UpperCamelCase   =	f.readlines()

		UpperCamelCase   =	F"class {class_name}("
		UpperCamelCase   =	F"{4 * ' '}def {test_name}("
		UpperCamelCase   =	F"{8 * ' '}{correct_line.split()[0]}"
		UpperCamelCase   =	F"{16 * ' '}{correct_line.split()[0]}"
		UpperCamelCase   =	False
		UpperCamelCase   =	False
		UpperCamelCase   =	False
		UpperCamelCase   =	False
		UpperCamelCase   =	0
		UpperCamelCase   =	0

		UpperCamelCase   =	[]
		for line in lines:
				if line.startswith(_SCREAMING_SNAKE_CASE    ):
						UpperCamelCase   =	True
				elif in_class and line.startswith(_SCREAMING_SNAKE_CASE    ):
						UpperCamelCase   =	True
				elif in_class and in_func and (line.startswith(_SCREAMING_SNAKE_CASE    ) or line.startswith(_SCREAMING_SNAKE_CASE    )):
						UpperCamelCase   =	len(line.split(correct_line.split()[0]    )[0]    )
						count += 1

						if count == done_test[_id]:
								UpperCamelCase   =	True

				if in_class and in_func and in_line:
						if ")" not in line:
								continue
						else:
								UpperCamelCase   =	True

				if in_class and in_func and in_line and insert_line:
						new_lines.append(F"{spaces * ' '}{correct_line}"    )
						UpperCamelCase   =	UpperCamelCase   =	UpperCamelCase   =	UpperCamelCase   =	False
				else:
						new_lines.append(_SCREAMING_SNAKE_CASE    )

		with open(_SCREAMING_SNAKE_CASE  ,	"w"    ) as f:
				for line in new_lines:
						f.write(_SCREAMING_SNAKE_CASE    )


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE=None    ):




		"""simple docstring"""


		if fail is not None:
				with open(_SCREAMING_SNAKE_CASE  ,	"r"    ) as f:
						UpperCamelCase   =	{l.strip() for l in f.readlines()}
		else:
				UpperCamelCase   =	None

		with open(_SCREAMING_SNAKE_CASE  ,	"r"    ) as f:
				UpperCamelCase   =	f.readlines()

		UpperCamelCase   =	defaultdict(_SCREAMING_SNAKE_CASE    )
		for line in correct_lines:
				UpperCamelCase   ,				UpperCamelCase   ,				UpperCamelCase   ,				UpperCamelCase   =	line.split(";"    )
				if test_failures is None or "::".join([file, class_name, test_name]    ) in test_failures:
						overwrite_file(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
						lowerCAmelCase__     			=			argparse.ArgumentParser()
						parser.add_argument('''--correct_filename''', help='''filename of tests with expected result''')
						parser.add_argument('''--fail_filename''', help='''filename of test failures''', type=str, default=None)
						lowerCAmelCase__     			=			parser.parse_args()

						main(args.correct_filename, args.fail_filename)






