

"""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


__UpperCamelCase  :      List[str]							      =		(
    '''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   __SCREAMING_SNAKE_CASE  (      A_						,     A_ ):
	warnings.warn(A_						,     A_ )
	requires_backends(A_						,     '''sklearn''' )
	return (preds == labels).mean()

def   __SCREAMING_SNAKE_CASE  (      A_						,     A_ ):
	warnings.warn(A_						,     A_ )
	requires_backends(A_						,     '''sklearn''' )
	lowerCAmelCase__	:						Optional[Any]  				=	simple_accuracy(A_						,     A_ )
	lowerCAmelCase__	:						List[Any]  				=	fa_score(y_true=A_						,     y_pred=A_ )
	return {
	    "acc": acc,
	    "f1": fa,
	    "acc_and_f1": (acc + fa) / 2,
	}

def   __SCREAMING_SNAKE_CASE  (      A_						,     A_ ):
	warnings.warn(A_						,     A_ )
	requires_backends(A_						,     '''sklearn''' )
	lowerCAmelCase__	:						Dict  				=	pearsonr(A_						,     A_ )[0]
	lowerCAmelCase__	:						List[Any]  				=	spearmanr(A_						,     A_ )[0]
	return {
	    "pearson": pearson_corr,
	    "spearmanr": spearman_corr,
	    "corr": (pearson_corr + spearman_corr) / 2,
	}

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





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







"""simple docstring"""





import os
from collections.abc import Iterator

def   __SCREAMING_SNAKE_CASE  (      A_ = "." ):
	for dir_path, dir_names, filenames in os.walk(A_ ):
		lowerCAmelCase__	:						str  				=	[d for d in dir_names if d != '''scripts''' and d[0] not in '''._''']
		for filename in filenames:
			if filename == "__init__.py":
				continue
			if os.path.splitext(A_ )[1] in (".py", ".ipynb"):
				yield os.path.join(A_						,     A_ ).lstrip('''./''' )

def   __SCREAMING_SNAKE_CASE  (      A_ ):
	return f'{i * "  "}*' if i else "\n##"

def   __SCREAMING_SNAKE_CASE  (      A_						,     A_ ):
	lowerCAmelCase__	:						Optional[Any]  				=	old_path.split(os.sep )
	for i, new_part in enumerate(new_path.split(os.sep ) ):
		if (i + 1 > len(A_ ) or old_parts[i] != new_part) and new_part:
			print(f'{md_prefix(A_ )} {new_part.replace("_"						,     " " ).title()}' )
	return new_path

def   __SCREAMING_SNAKE_CASE  (      A_ = "." ):
	lowerCAmelCase__	:						Any  				=	''''''
	for filepath in sorted(good_file_paths(A_ ) ):
		lowerCAmelCase__				,lowerCAmelCase__	:						str  				=	os.path.split(A_ )
		if filepath != old_path:
			lowerCAmelCase__	:						str  				=	print_path(A_						,     A_ )
		lowerCAmelCase__	:						str  				=	(filepath.count(os.sep ) + 1) if filepath else 0
		lowerCAmelCase__	:						Union[str, Any]  				=	f'{filepath}/{filename}'.replace(''' '''						,     '''%20''' )
		lowerCAmelCase__	:						List[str]  				=	os.path.splitext(filename.replace('''_'''						,     ''' ''' ).title() )[0]
		print(f'{md_prefix(A_ )} [{filename}]({url})' )


if __name__ == "__main__":
							print_directory_md('''.''')




