




from __future__ import annotations

from collections.abc import Iterator


class    lowerCamelCase    :






			'''simple docstring'''





			def __init__( self			:   List[Any]       ,						lowerCamelCase_			:   int  )						->   None:
								__magic_name__							:	Optional[int]    							=							value
								__magic_name__							:	Node | None    							=							None
								__magic_name__							:	Node | None    							=							None






class    lowerCamelCase    :






			'''simple docstring'''





			def __init__( self			:   Tuple       ,						lowerCamelCase_			:   Node  )						->   None:
								__magic_name__							:	int    							=							tree

			def 							UpperCAmelCase__       ( self			:   str       ,						lowerCamelCase_			:   Node | None  )						->   int:
								if node is None:
													return 0
								return node.value + (
								    self.depth_first_search(node.left  ) + self.depth_first_search(node.right  )
								)


			def __iter__( self			:   Optional[Any]  )						->   Iterator[int]:
								yield self.depth_first_search(self.tree  )


if __name__ == "__main__":
			import doctest

			doctest.testmod()









from typing import TYPE_CHECKING

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


__lowerCamelCase   :						int				=			{'''configuration_swin''': ['''SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SwinConfig''', '''SwinOnnxConfig''']}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowerCamelCase   :						int				=			[
	    '''SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''SwinForImageClassification''',
	    '''SwinForMaskedImageModeling''',
	    '''SwinModel''',
	    '''SwinPreTrainedModel''',
	    '''SwinBackbone''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__lowerCamelCase   :						Optional[int]				=			[
	    '''TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFSwinForImageClassification''',
	    '''TFSwinForMaskedImageModeling''',
	    '''TFSwinModel''',
	    '''TFSwinPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_swin import (
		    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SwinBackbone,
		    SwinForImageClassification,
		    SwinForMaskedImageModeling,
		    SwinModel,
		    SwinPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_swin import (
		    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFSwinForImageClassification,
		    TFSwinForMaskedImageModeling,
		    TFSwinModel,
		    TFSwinPreTrainedModel,
		)

else:
	import sys

	__lowerCamelCase   :						Union[str, Any]				=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



