



'''simple docstring'''



from __future__ import annotations






class 			_SCREAMING_SNAKE_CASE				:



			def __init__(     self		:						Dict    ,			__UpperCamelCase		:						int = 0			)      ->      None:
							"""simple docstring"""





							snake_case__      :   Union[str, Any]      =    value
							snake_case__      :   Node | None      =    None
							snake_case__      :   Node | None      =    None



def 							__UpperCAmelCase				(				UpperCamelCase__				:Node | None   ,				UpperCamelCase__				:Node | None			)		->						int:
				if treea is None:
								return treea
				if treea is None:
								return treea

				snake_case__      :   Optional[Any]      =    treea.value + treea.value
				snake_case__      :   Optional[int]      =    merge_two_binary_trees(treea.left   ,				treea.left			)
				snake_case__      :   Dict      =    merge_two_binary_trees(treea.right   ,				treea.right			)
				return treea


def 							__UpperCAmelCase				(				UpperCamelCase__				:Node | None			)		->						List[Any]:
				if root:
								print(root.value			)
								print_preorder(root.left			)
								print_preorder(root.right			)


if __name__ == "__main__":
				_lowercase       :						int						=Node(1)
				_lowercase       :						Union[str, Any]						=Node(2)
				_lowercase       :						List[Any]						=Node(3)
				_lowercase       :						Tuple						=Node(4)

				_lowercase       :						Optional[Any]						=Node(2)
				_lowercase       :						int						=Node(4)
				_lowercase       :						List[Any]						=Node(6)
				_lowercase       :						Any						=Node(9)
				_lowercase       :						Optional[Any]						=Node(5)

				print("Tree1 is: ")
				print_preorder(treea)
				print("Tree2 is: ")
				print_preorder(treea)
				_lowercase       :						Tuple						=merge_two_binary_trees(treea, treea)
				print("Merged Tree is: ")
				print_preorder(merged_tree)









"""simple docstring"""






from typing import TYPE_CHECKING

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


_lowercase					:					Any 		=		{
    "configuration_unispeech_sat": ["UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechSatConfig"],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase					:					Any 		=		[
		    "UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "UniSpeechSatForAudioFrameClassification",
		    "UniSpeechSatForCTC",
		    "UniSpeechSatForPreTraining",
		    "UniSpeechSatForSequenceClassification",
		    "UniSpeechSatForXVector",
		    "UniSpeechSatModel",
		    "UniSpeechSatPreTrainedModel",
		]

if TYPE_CHECKING:
		from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_unispeech_sat import (
				    UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    UniSpeechSatForAudioFrameClassification,
				    UniSpeechSatForCTC,
				    UniSpeechSatForPreTraining,
				    UniSpeechSatForSequenceClassification,
				    UniSpeechSatForXVector,
				    UniSpeechSatModel,
				    UniSpeechSatPreTrainedModel,
				)

else:
		import sys

		_lowercase					:					int 		=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




