



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     _UpperCAmelCase			(       unittest.TestCase     ):




     def 		snake_case_		(				self):
         A__		 =					torch.tensor([-1_0_0, -1, -0.1, 0, 0.1, 1.0, 1_0_0])
         A__		 =					get_activation('''gelu''')
         self.assertTrue(torch.allclose(gelu_python(UpperCAmelCase__) ,						torch_builtin(UpperCAmelCase__)))
         self.assertFalse(torch.allclose(gelu_python(UpperCAmelCase__) ,						gelu_new(UpperCAmelCase__)))




     def 		snake_case_		(				self):
         A__		 =					torch.tensor([-1_0_0, -1, -0.1, 0, 0.1, 1.0, 1_0_0])
         A__		 =					get_activation('''gelu''')
         A__		 =					get_activation('''gelu_10''')

         A__		 =					torch_builtin(UpperCAmelCase__)
         A__		 =					geluaa(UpperCAmelCase__)

         A__		 =					torch.where(y_gelu_aa < 1_0.0 ,						1 ,						0)

         self.assertTrue(torch.max(UpperCAmelCase__).item() == 1_0.0)
         self.assertTrue(torch.allclose(y_gelu * clipped_mask ,						y_gelu_aa * clipped_mask))




     def 		snake_case_		(				self):
         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 		snake_case_		(				self):
         A__		 =					get_activation('''gelu''')
         A__		 =					1
         A__		 =					get_activation('''gelu''')
         self.assertEqual(acta.a ,						1)
         with self.assertRaises(UpperCAmelCase__):
             A__		 =					acta.a







from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowercase						  =		logging.get_logger(__name__)



class     _UpperCAmelCase			(       A__     ):
     UpperCamelCase__		    =				'''timm_backbone'''




     def __init__(				self ,						a__=None ,						a__=3 ,						a__=True ,						a__=True ,						a__=None ,						**a__ ,						):
         super().__init__(**a__)
         A__		 =					backbone
         A__		 =					num_channels
         A__		 =					features_only
         A__		 =					use_pretrained_backbone
         A__		 =					True
         A__		 =					out_indices if out_indices is not None else (-1,)
