
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
			import torch

			from transformers.activations import gelu_new, gelu_python, get_activation





@require_torch
class 	_lowerCAmelCase					(	unittest.TestCase       ):




				def      __a						(					self     )				->      str:
							lowerCAmelCase_						=	torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]     )
							lowerCAmelCase_						=	get_activation("gelu"     )
							self.assertTrue(torch.allclose(gelu_python(_UpperCamelCase     )				,				torch_builtin(_UpperCamelCase     )     )     )
							self.assertFalse(torch.allclose(gelu_python(_UpperCamelCase     )				,				gelu_new(_UpperCamelCase     )     )     )




				def      __a						(					self     )				->      Any:
							lowerCAmelCase_						=	torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]     )
							lowerCAmelCase_						=	get_activation("gelu"     )
							lowerCAmelCase_						=	get_activation("gelu_10"     )

							lowerCAmelCase_						=	torch_builtin(_UpperCamelCase     )
							lowerCAmelCase_						=	geluaa(_UpperCamelCase     )

							lowerCAmelCase_						=	torch.where(y_gelu_aa < 10.0				,				1				,				0     )

							self.assertTrue(torch.max(_UpperCamelCase     ).item() == 10.0     )
							self.assertTrue(torch.allclose(y_gelu * clipped_mask				,				y_gelu_aa * clipped_mask     )     )




				def      __a						(					self     )				->      List[Any]:
							get_activation("gelu"     )
							get_activation("gelu_10"     )
							get_activation("gelu_fast"     )
							get_activation("gelu_new"     )
							get_activation("gelu_python"     )
							get_activation("gelu_pytorch_tanh"     )
							get_activation("linear"     )
							get_activation("mish"     )
							get_activation("quick_gelu"     )
							get_activation("relu"     )
							get_activation("sigmoid"     )
							get_activation("silu"     )
							get_activation("swish"     )
							get_activation("tanh"     )
							with self.assertRaises(_UpperCamelCase     ):
										get_activation("bogus"     )
							with self.assertRaises(_UpperCamelCase     ):
										get_activation(_UpperCamelCase     )




				def      __a						(					self     )				->      Optional[int]:
							lowerCAmelCase_						=	get_activation("gelu"     )
							lowerCAmelCase_						=	1
							lowerCAmelCase_						=	get_activation("gelu"     )
							self.assertEqual(acta.a				,				1     )
							with self.assertRaises(_UpperCamelCase     ):
										lowerCAmelCase_						=	acta.a





import functools






def    lowerCamelCase__				(				__lowerCAmelCase  :  str    ,							__lowerCAmelCase  :  str				):




			"""simple docstring"""


			lowerCAmelCase_						=	len(__lowerCAmelCase				)
			lowerCAmelCase_						=	len(__lowerCAmelCase				)

			@functools.cache
			def min_distance(__lowerCAmelCase  :  int    ,							__lowerCAmelCase  :  int				) -> int:
						# if first word index is overflow - delete all from the second word
						if indexa >= len_worda:
									return len_worda - indexa
						# if second word index is overflow - delete all from the first word
						if indexa >= len_worda:
									return len_worda - indexa
						lowerCAmelCase_						=	int(worda[indexa] != worda[indexa]				)  # current letters not identical
						return min(
						    1 + min_distance(indexa + 1    ,							__lowerCAmelCase				)    ,							1 + min_distance(__lowerCAmelCase    ,							indexa + 1				)    ,							diff + min_distance(indexa + 1    ,							indexa + 1				)    ,							)

			return min_distance(0    ,							0				)


if __name__ == "__main__":
			import doctest

			doctest.testmod()



