


"""simple docstring"""
from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE					:       List[Any]							   =							{
    '''configuration_flava''': [
        '''FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''FlavaConfig''',
        '''FlavaImageCodebookConfig''',
        '''FlavaImageConfig''',
        '''FlavaMultimodalConfig''',
        '''FlavaTextConfig''',
    ],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			SCREAMING_SNAKE_CASE					:       Tuple							   =							['''FlavaFeatureExtractor''']
			SCREAMING_SNAKE_CASE					:       int							   =							['''FlavaImageProcessor''']
			SCREAMING_SNAKE_CASE					:       Optional[int]							   =							['''FlavaProcessor''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			SCREAMING_SNAKE_CASE					:       Tuple							   =							[
			    '''FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''FlavaForPreTraining''',
			    '''FlavaImageCodebook''',
			    '''FlavaImageModel''',
			    '''FlavaModel''',
			    '''FlavaMultimodalModel''',
			    '''FlavaPreTrainedModel''',
			    '''FlavaTextModel''',
			]

if TYPE_CHECKING:
			from .configuration_flava import (
			    FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    FlavaConfig,
			    FlavaImageCodebookConfig,
			    FlavaImageConfig,
			    FlavaMultimodalConfig,
			    FlavaTextConfig,
			)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_flava import FlavaFeatureExtractor
						from .image_processing_flava import FlavaImageProcessor
						from .processing_flava import FlavaProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flava import (
						    FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST,
						    FlavaForPreTraining,
						    FlavaImageCodebook,
						    FlavaImageModel,
						    FlavaModel,
						    FlavaMultimodalModel,
						    FlavaPreTrainedModel,
						    FlavaTextModel,
						)

else:
			import sys

			SCREAMING_SNAKE_CASE					:       Optional[Any]							   =							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










'''simple docstring'''

from __future__ import annotations



class 		lowerCamelCase__   :




					'''simple docstring'''



					def __init__(	self					:						str  ,	UpperCamelCase_					:						int       )	->							None:



						'''simple docstring'''





						_lowercase       :							Any  	=		value
						_lowercase       :							Node | None  	=		None
						_lowercase       :							Node | None  	=		None






class 		lowerCamelCase__   :




					'''simple docstring'''



					A_         =    42




					def __init__(	self					:						List[Any]       )	->							None:



						'''simple docstring'''





						_lowercase       :							Optional[int]  	=		0




					def     __UpperCAmelCase  (	self					:						str  ,	UpperCamelCase_					:						Node | None  ,	UpperCamelCase_					:						int       )	->							None:



						'''simple docstring'''





						if node is None:
							return

						if path_sum == self.target:
							self.paths += 1

						if node.left:
							self.depth_first_search(node.left  ,	path_sum + node.left.value       )
						if node.right:
							self.depth_first_search(node.right  ,	path_sum + node.right.value       )




					def     __UpperCAmelCase  (	self					:						Optional[int]  ,	UpperCamelCase_					:						Node | None  ,	UpperCamelCase_					:						int | None = None       )	->							int:



						'''simple docstring'''





						if node is None:
							return 0
						if target is not None:
							_lowercase       :							Union[str, Any]  	=		target

						self.depth_first_search(UpperCamelCase_  ,	node.value       )
						self.path_sum(node.left       )
						self.path_sum(node.right       )

						return self.paths


if __name__ == "__main__":
		import doctest

		doctest.testmod()
