
from __future__ import annotations

from enum import Enum



class       a_   ( _a						):
			a  : Optional[int]				      =       2_4
			a  : Optional[int]				      =       2_1
			a  : int				      =       1_8
			a  : Any				      =       1_5
			a  : Tuple				      =       1_2
			a  : Optional[int]				      =       9
			a  : Optional[Any]				      =       6
			a  : int				      =       3
			a  : Optional[int]				      =       2
			a  : int				      =       1
			a  : int				      =       -1
			a  : int				      =       -2
			a  : Dict				      =       -3
			a  : int				      =       -6
			a  : Any				      =       -9
			a  : int				      =       -1_2
			a  : Any				      =       -1_5
			a  : Optional[Any]				      =       -1_8
			a  : Optional[int]				      =       -2_1
			a  : Optional[int]				      =       -2_4







class       a_   ( _a						):
			a  : Any				      =       8
			a  : Optional[int]				      =       7
			a  : Dict				      =       6
			a  : int				      =       5
			a  : Optional[int]				      =       4
			a  : Dict				      =       3
			a  : str				      =       2
			a  : Optional[Any]				      =       1







def   UpperCamelCase__     (    SCREAMING_SNAKE_CASE_  :  float		,      SCREAMING_SNAKE_CASE_  :  str | SIUnit		,      SCREAMING_SNAKE_CASE_  :  str | SIUnit		,      )     ->    float:
						if isinstance(SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_					):
												_lowercase									=				SIUnit[known_prefix.lower()]
						if isinstance(SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_					):
												_lowercase									=				SIUnit[unknown_prefix.lower()]
						_lowercase									=				known_amount * (
						    10 ** (known_prefix.value - unknown_prefix.value)
						)
						return unknown_amount




def   UpperCamelCase__     (    SCREAMING_SNAKE_CASE_  :  float		,      SCREAMING_SNAKE_CASE_  :  str | BinaryUnit		,      SCREAMING_SNAKE_CASE_  :  str | BinaryUnit		,      )     ->    float:
						if isinstance(SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_					):
												_lowercase									=				BinaryUnit[known_prefix.lower()]
						if isinstance(SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_					):
												_lowercase									=				BinaryUnit[unknown_prefix.lower()]
						_lowercase									=				known_amount * (
						    2 ** ((known_prefix.value - unknown_prefix.value) * 10)
						)
						return unknown_amount


if __name__ == "__main__":
		import doctest

		doctest.testmod()

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A		:   int         =    {'''configuration_vilt''': ['''VILT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViltConfig''']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A		:   int         =    ['''ViltFeatureExtractor''']
		A		:   List[Any]         =    ['''ViltImageProcessor''']
		A		:   Dict         =    ['''ViltProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A		:   Tuple         =    [
		    '''VILT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ViltForImageAndTextRetrieval''',
		    '''ViltForImagesAndTextClassification''',
		    '''ViltForTokenClassification''',
		    '''ViltForMaskedLM''',
		    '''ViltForQuestionAnswering''',
		    '''ViltLayer''',
		    '''ViltModel''',
		    '''ViltPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_vilt import ViltFeatureExtractor
				from .image_processing_vilt import ViltImageProcessor
				from .processing_vilt import ViltProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_vilt import (
				    VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ViltForImageAndTextRetrieval,
				    ViltForImagesAndTextClassification,
				    ViltForMaskedLM,
				    ViltForQuestionAnswering,
				    ViltForTokenClassification,
				    ViltLayer,
				    ViltModel,
				    ViltPreTrainedModel,
				)


else:
		import sys

		A		:   Dict         =    _LazyModule(__name__, globals()['''__file__'''], _import_structure)