from __future__ import annotations



class 					snake_case__       :



			def __init__(				self   :   Optional[Any]			,	A__   :   int = 0   )							->     None:




									'''simple docstring'''




									snake_case_     :			Optional[int]       =       value
									snake_case_     :			Node | None       =       None
									snake_case_     :			Node | None       =       None






def 					SCREAMING_SNAKE_CASE_			(		lowerCAmelCase_: Node | None ,	lowerCAmelCase_: Node | None     ):
						if treea is None:
												return treea
						if treea is None:
												return treea

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






def 					SCREAMING_SNAKE_CASE_			(		lowerCAmelCase_: Node | None     ):
						if root:
												print(root.value     )
												print_preorder(root.left     )
												print_preorder(root.right     )


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

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

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




from typing import TYPE_CHECKING

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


UpperCAmelCase							=       {
    "configuration_nystromformer": ["NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "NystromformerConfig"],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase							=       [
         "NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
         "NystromformerForMaskedLM",
         "NystromformerForMultipleChoice",
         "NystromformerForQuestionAnswering",
         "NystromformerForSequenceClassification",
         "NystromformerForTokenClassification",
         "NystromformerLayer",
         "NystromformerModel",
         "NystromformerPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_nystromformer import (
              NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              NystromformerForMaskedLM,
              NystromformerForMultipleChoice,
              NystromformerForQuestionAnswering,
              NystromformerForSequenceClassification,
              NystromformerForTokenClassification,
              NystromformerLayer,
              NystromformerModel,
              NystromformerPreTrainedModel,
          )


else:
     import sys

     UpperCAmelCase							=       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



