


'''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 							__UpperCamelCase    (		unittest.TestCase ):




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	int    =  torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]							)
						__a      :	Tuple    =  get_activation('gelu'							)
						self.assertTrue(torch.allclose(gelu_python(__a							)						,    torch_builtin(__a							)							)							)
						self.assertFalse(torch.allclose(gelu_python(__a							)						,    gelu_new(__a							)							)							)




	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	Tuple    =  torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]							)
						__a      :	Any    =  get_activation('gelu'							)
						__a      :	List[str]    =  get_activation('gelu_10'							)

						__a      :	Tuple    =  torch_builtin(__a							)
						__a      :	Any    =  geluaa(__a							)

						__a      :	Optional[Any]    =  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 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						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 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





						__a      :	List[str]    =  get_activation('gelu'							)
						__a      :	List[str]    =  1
						__a      :	str    =  get_activation('gelu'							)
						self.assertEqual(acta.a						,    1							)
						with self.assertRaises(__a							):
											__a      :	List[str]    =  acta.a







'''simple docstring'''



from __future__ import annotations

from dataclasses import dataclass





@dataclass
class 							__UpperCamelCase    :
	A_           =   42
	A_           =   None
	A_           =   None






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       TreeNode | None       ):

					# Validation
					def is_valid_tree(_SCREAMING_SNAKE_CASE				:       TreeNode | None       ) -> bool:
										if node is None:
															return True

										if not isinstance(_SCREAMING_SNAKE_CASE						,				_SCREAMING_SNAKE_CASE       ):
															return False

										try:
															float(node.data       )
										except (TypeError, ValueError):
															return False

										return is_valid_tree(node.left       ) and is_valid_tree(node.right       )

					if not is_valid_tree(_SCREAMING_SNAKE_CASE       ):
										raise ValueError(
										    'Each node should be type of TreeNode and data should be float.'       )

					def is_binary_search_tree_recursive_check(
					    _SCREAMING_SNAKE_CASE				:       TreeNode | None						,				_SCREAMING_SNAKE_CASE				:       float						,				_SCREAMING_SNAKE_CASE				:       float       ) -> bool:

										if node is None:
															return True

										return (
										    left_bound < node.data < right_bound
										    and is_binary_search_tree_recursive_check(node.left						,				_SCREAMING_SNAKE_CASE						,				node.data       )
										    and is_binary_search_tree_recursive_check(
										        node.right						,				node.data						,				_SCREAMING_SNAKE_CASE       )
										)

					return is_binary_search_tree_recursive_check(_SCREAMING_SNAKE_CASE						,				-float('inf'       )						,				float('inf'       )       )


if __name__ == "__main__":
	import doctest

	doctest.testmod()



