

class      lowerCamelCase_ :




 def __init__(			self  ,  _UpperCAmelCase							):
   __UpperCAmelCase	:  Any		=     data
   __UpperCAmelCase	:  BinaryTreeNode | None		=     None
   __UpperCAmelCase	:  BinaryTreeNode | None		=     None





def  _snake_case		(snake_case_					:     BinaryTreeNode | None    ,       snake_case_					:     int  )							->		BinaryTreeNode | None:
  if node is None:
    __UpperCAmelCase	:  List[Any]		=     BinaryTreeNode(snake_case_  )
    return node

  # binary search tree is not empty,
  # so we will insert it into the tree
  # if new_value is less than value of data in node,
  #  add it to left subtree and proceed recursively
  if new_value < node.data:
    __UpperCAmelCase	:  Union[str, Any]		=     insert(node.left_child    ,       snake_case_  )
  else:
    # if new_value is greater than value of data in node,
    #  add it to right subtree and proceed recursively
    __UpperCAmelCase	:  Tuple		=     insert(node.right_child    ,       snake_case_  )
  return node





def  _snake_case		(snake_case_					:     None | BinaryTreeNode  )							->		list[int]:  # if node is None,return
  if node:
    __UpperCAmelCase	:  str		=     inorder(node.left_child  )
    __UpperCAmelCase	:  Optional[int]		=     [*inorder_array, node.data]
    __UpperCAmelCase	:  str		=     inorder_array + inorder(node.right_child  )
  else:
    __UpperCAmelCase	:  Union[str, Any]		=     []
  return inorder_array





def  _snake_case		()							->		BinaryTreeNode | None:
  __UpperCAmelCase	:  Tuple		=     insert(snake_case_    ,       15  )
  insert(snake_case_    ,       10  )
  insert(snake_case_    ,       25  )
  insert(snake_case_    ,       6  )
  insert(snake_case_    ,       14  )
  insert(snake_case_    ,       20  )
  insert(snake_case_    ,       60  )
  return root





def  _snake_case		()							->		None:
  # main function
  __UpperCAmelCase	:  Any		=     make_tree()
  print('Printing values of binary search tree in Inorder Traversal.'  )
  inorder(snake_case_  )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()







"""simple docstring"""






from typing import TYPE_CHECKING

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


UpperCamelCase_						   =   {
    'configuration_sam': [
        'SAM_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SamConfig',
        'SamMaskDecoderConfig',
        'SamPromptEncoderConfig',
        'SamVisionConfig',
    ],
    'processing_sam': ['SamProcessor'],
}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase_						   =   [
          'SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
          'SamModel',
          'SamPreTrainedModel',
      ]
try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase_						   =   [
          'TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
          'TFSamModel',
          'TFSamPreTrainedModel',
      ]
try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase_						   =   ['SamImageProcessor']


if TYPE_CHECKING:
      from .configuration_sam import (
          SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
          SamConfig,
          SamMaskDecoderConfig,
          SamPromptEncoderConfig,
          SamVisionConfig,
      )
      from .processing_sam import SamProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_sam import SamImageProcessor

else:
      import sys

      UpperCamelCase_						   =   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)