'''simple docstring'''




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     __magic_name__						(    unittest.TestCase):







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[Any]    ):
										lowercase_					:			Union[str, Any]										=       torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]    )
										lowercase_					:			str										=       get_activation("""gelu"""    )
										self.assertTrue(torch.allclose(gelu_python(__a    )				,			torch_builtin(__a    )    )    )
										self.assertFalse(torch.allclose(gelu_python(__a    )				,			gelu_new(__a    )    )    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[str]    ):
										lowercase_					:			List[str]										=       torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]    )
										lowercase_					:			Tuple										=       get_activation("""gelu"""    )
										lowercase_					:			Any										=       get_activation("""gelu_10"""    )

										lowercase_					:			List[str]										=       torch_builtin(__a    )
										lowercase_					:			Any										=       geluaa(__a    )

										lowercase_					:			str										=       torch.where(y_gelu_aa < 10.0				,			1				,			0    )

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







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[int]    ):
										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(__a    ):
																	get_activation("""bogus"""    )
										with self.assertRaises(__a    ):
																	get_activation(__a    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[Any]    ):
										lowercase_					:			str										=       get_activation("""gelu"""    )
										lowercase_					:			Union[str, Any]										=       1
										lowercase_					:			Union[str, Any]										=       get_activation("""gelu"""    )
										self.assertEqual(acta.a				,			1    )
										with self.assertRaises(__a    ):
																	lowercase_					:			Union[str, Any]										=       acta.a






'''simple docstring'''





import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


SCREAMING_SNAKE_CASE_:     Union[str, Any]  =logging.get_logger(__name__)




class        __A      ( UpperCamelCase__	):



    def __init__(self    :    int   ,			*__a    :    Dict   ,			**__a    :    str ):
         warnings.warn(
             "The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
             " use CLIPImageProcessor instead."   ,			__a   ,			)
         super().__init__(*__a   ,			**__a )




