






'''simple docstring'''





from typing import TYPE_CHECKING

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


a_     :   List[str]      = {
    'configuration_mobilenet_v1': [
        'MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileNetV1Config',
        'MobileNetV1OnnxConfig',
    ],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a_     :   Union[str, Any]      = ['MobileNetV1FeatureExtractor']
							a_     :   List[Any]      = ['MobileNetV1ImageProcessor']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a_     :   Optional[Any]      = [
							    'MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'MobileNetV1ForImageClassification',
							    'MobileNetV1Model',
							    'MobileNetV1PreTrainedModel',
							    'load_tf_weights_in_mobilenet_v1',
							]


if TYPE_CHECKING:
							from .configuration_mobilenet_va import (
							    MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    MobileNetVaConfig,
							    MobileNetVaOnnxConfig,
							)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
														from .image_processing_mobilenet_va import MobileNetVaImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mobilenet_va import (
														    MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MobileNetVaForImageClassification,
														    MobileNetVaModel,
														    MobileNetVaPreTrainedModel,
														    load_tf_weights_in_mobilenet_va,
														)


else:
							import sys

							a_     :   Optional[int]      = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)











'''simple docstring'''





from __future__ import annotations





class 		SCREAMING_SNAKE_CASE__   :



		def __init__(    self:    List[str]				,   a:    int = 0)  ->None:






								'''simple docstring'''


								a_				     =   value
								a_				     =   None
								a_				     =   None





def 			__UpperCAmelCase				(lowercase__	,lowercase__				)		->				Node | None:

						'''simple docstring'''


						if treea is None:
												return treea
						if treea is None:
												return treea

						a_				     =   treea.value + treea.value
						a_				     =   merge_two_binary_trees(treea.left	,treea.left				)
						a_				     =   merge_two_binary_trees(treea.right	,treea.right				)
						return treea



def 			__UpperCAmelCase				(lowercase__				)		->				None:

						'''simple docstring'''


						if root:
												print(root.value				)
												print_preorder(root.left				)
												print_preorder(root.right				)


if __name__ == "__main__":
							a_      = Node(1)
							a_      = Node(2)
							a_      = Node(3)
							a_      = Node(4)

							a_      = Node(2)
							a_      = Node(4)
							a_      = Node(6)
							a_      = Node(9)
							a_      = Node(5)

							print('Tree1 is: ')
							print_preorder(treea)
							print('Tree2 is: ')
							print_preorder(treea)
							a_      = merge_two_binary_trees(treea, treea)
							print('Merged Tree is: ')
							print_preorder(merged_tree)



