


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase__  :Tuple             =							{'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__  :List[Any]             =							['''BeitFeatureExtractor''']
						lowerCAmelCase__  :Optional[Any]             =							['''BeitImageProcessor''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__  :int             =							[
						    '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''BeitForImageClassification''',
						    '''BeitForMaskedImageModeling''',
						    '''BeitForSemanticSegmentation''',
						    '''BeitModel''',
						    '''BeitPreTrainedModel''',
						]


try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__  :Tuple             =							[
						    '''FlaxBeitForImageClassification''',
						    '''FlaxBeitForMaskedImageModeling''',
						    '''FlaxBeitModel''',
						    '''FlaxBeitPreTrainedModel''',
						]

if TYPE_CHECKING:
						from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_beit import BeitFeatureExtractor
												from .image_processing_beit import BeitImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_beit import (
												    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BeitForImageClassification,
												    BeitForMaskedImageModeling,
												    BeitForSemanticSegmentation,
												    BeitModel,
												    BeitPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_beit import (
												    FlaxBeitForImageClassification,
												    FlaxBeitForMaskedImageModeling,
												    FlaxBeitModel,
												    FlaxBeitPreTrainedModel,
												)


else:
						import sys

						lowerCAmelCase__  :Dict             =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




import math
import random

def 	lowerCAmelCase__			(      a__:		float      ,  a__:		bool = False	)  ->		float:


							'''simple docstring'''





							if deriv:
														return value * (1 - value)
							return 1 / (1 + math.exp(-value	))


# Initial Value
lowerCAmelCase__  :Optional[Any]             =							0.02

def 	lowerCAmelCase__			(      a__:		int      ,  a__:		int	)  ->		float:


							'''simple docstring'''





							_UpperCAmelCase					=      float(2 * (random.randint(1      ,  1_0_0	)) - 1	)

							for _ in range(a__	):
														# Forward propagation
														_UpperCAmelCase					=      sigmoid_function(INITIAL_VALUE * weight	)
														# How much did we miss?
														_UpperCAmelCase					=      (expected / 1_0_0) - layer_a
														# Error delta
														_UpperCAmelCase					=      layer_1_error * sigmoid_function(a__      ,  a__	)
														# Update weight
														weight += INITIAL_VALUE * layer_1_delta

							return layer_a * 1_0_0


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		lowerCAmelCase__  :List[Any]             =							int(input('''Expected value: '''))
		lowerCAmelCase__  :Any             =							int(input('''Number of propagations: '''))
		print(forward_propagation(expected, number_propagations))
