


'''simple docstring'''





import os
import time

import pytest

from datasets.utils.filelock import FileLock, Timeout






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: Dict ):






			"""simple docstring"""




			__A=	FileLock(str(tmpdir / 'foo.lock' ) )
			__A=	FileLock(str(tmpdir / 'foo.lock' ) )
			__A=	0.01
			with locka.acquire():
						with pytest.raises(_SCREAMING_SNAKE_CASE ):
									__A=	time.time()
									locka.acquire(_SCREAMING_SNAKE_CASE )
									assert time.time() - _start > timeout






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: Any ):






			"""simple docstring"""




			__A=	'a' * 1000 + '.lock'
			__A=	FileLock(str(tmpdir / filename ) )
			assert locka._lock_file.endswith('.lock' )
			assert not locka._lock_file.endswith(_SCREAMING_SNAKE_CASE )
			assert len(os.path.basename(locka._lock_file ) ) <= 255
			__A=	FileLock(tmpdir / filename )
			with locka.acquire():
						with pytest.raises(_SCREAMING_SNAKE_CASE ):
									locka.acquire(0 )







'''simple docstring'''





import numpy as np

from transformers import Pipeline






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: Any ):






			"""simple docstring"""




			__A=	np.max(_SCREAMING_SNAKE_CASE,axis=-1,keepdims=_SCREAMING_SNAKE_CASE )
			__A=	np.exp(outputs - maxes )
			return shifted_exp / shifted_exp.sum(axis=-1,keepdims=_SCREAMING_SNAKE_CASE )






class 						a__					(					a_   ):





			'''simple docstring'''

			def 					lowerCAmelCase     (  self							:			Optional[Any]			,    **lowerCAmelCase_							:			List[str]	)      ->		List[str]:
						__A=	{}
						if "second_text" in kwargs:
									__A=	kwargs['second_text']
						return preprocess_kwargs, {}, {}
			def 					lowerCAmelCase     (  self							:			str			,    lowerCAmelCase_							:			Union[str, Any]			,    lowerCAmelCase_							:			Optional[int]=None	)      ->		int:
						return self.tokenizer(lowerCAmelCase_			,    text_pair=lowerCAmelCase_			,    return_tensors=self.framework	)
			def 					lowerCAmelCase     (  self							:			Dict			,    lowerCAmelCase_							:			List[str]	)      ->		Tuple:
						return self.model(**lowerCAmelCase_	)

			def 					lowerCAmelCase     (  self							:			str			,    lowerCAmelCase_							:			Dict	)      ->		Optional[int]:
						__A=	model_outputs.logits[0].numpy()
						__A=	softmax(lowerCAmelCase_	)

						__A=	np.argmax(lowerCAmelCase_	)
						__A=	self.model.config.idalabel[best_class]
						__A=	probabilities[best_class].item()
						__A=	logits.tolist()
						return {"label": label, "score": score, "logits": logits}



