from __future__ import annotations

from collections import defaultdict
from dataclasses import dataclass


@dataclass
class _lowercase					:





							"""simple docstring"""




							lowerCAmelCase__       =					42
							lowerCAmelCase__       =					None
							lowerCAmelCase__       =					None






def 					__lowerCAmelCase			(  ):



							"""simple docstring"""


							return TreeNode(3 ,TreeNode(9					) ,TreeNode(20 ,TreeNode(15					) ,TreeNode(7					)					)					)


def 					__lowerCAmelCase			(  _A					):



							"""simple docstring"""


							def depth_first_search(
							    _A ,_A ,_A					) -> None:
														if not root:
																					return

														if depth == len(_A					):
																					right_view.append(root.val					)

														depth_first_search(root.right ,depth + 1 ,_A					)
														depth_first_search(root.left ,depth + 1 ,_A					)

							_lowercase				=	[]
							if not root:
														return right_view

							depth_first_search(_A ,0 ,_A					)
							return right_view


def 					__lowerCAmelCase			(  _A					):



							"""simple docstring"""


							def depth_first_search(
							    _A ,_A ,_A					) -> None:
														if not root:
																					return

														if depth == len(_A					):
																					left_view.append(root.val					)

														depth_first_search(root.left ,depth + 1 ,_A					)
														depth_first_search(root.right ,depth + 1 ,_A					)

							_lowercase				=	[]
							if not root:
														return left_view

							depth_first_search(_A ,0 ,_A					)
							return left_view


def 					__lowerCAmelCase			(  _A					):



							"""simple docstring"""


							def breadth_first_search(_A ,_A					) -> None:
														_lowercase				=	[(root, 0)]
														_lowercase				=	defaultdict(_A					)

														while queue:
																					_lowercase				=	queue.pop(0					)
																					_lowercase				,       _lowercase				=	first

																					lookup[hd].append(node.val					)

																					if node.left:
																												queue.append((node.left, hd - 1)					)
																					if node.right:
																												queue.append((node.right, hd + 1)					)

														for pair in sorted(lookup.items() ,key=lambda _A					: each[0]					):
																					top_view.append(pair[1][0]					)

							_lowercase				=	[]
							if not root:
														return top_view

							breadth_first_search(_A ,_A					)
							return top_view


def 					__lowerCAmelCase			(  _A					):



							"""simple docstring"""


							from collections import defaultdict

							def breadth_first_search(_A ,_A					) -> None:
														_lowercase				=	[(root, 0)]
														_lowercase				=	defaultdict(_A					)

														while queue:
																					_lowercase				=	queue.pop(0					)
																					_lowercase				,       _lowercase				=	first
																					lookup[hd].append(node.val					)

																					if node.left:
																												queue.append((node.left, hd - 1)					)
																					if node.right:
																												queue.append((node.right, hd + 1)					)

														for pair in sorted(lookup.items() ,key=lambda _A					: each[0]					):
																					bottom_view.append(pair[1][-1]					)

							_lowercase				=	[]
							if not root:
														return bottom_view

							breadth_first_search(_A ,_A					)
							return bottom_view


if __name__ == "__main__":
		import doctest

		doctest.testmod()



import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


A_:      Tuple        =			logging.get_logger(__name__)


class _lowercase					(       _UpperCAmelCase						):





							"""simple docstring"""




							def __init__(    self     ,   *UpperCAmelCase     ,   **UpperCAmelCase  ):







														'''simple docstring'''






														warnings.warn(
														    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
														    """ Please use MobileNetV2ImageProcessor instead."""     ,   UpperCAmelCase     ,   )
														super().__init__(*UpperCAmelCase     ,   **UpperCAmelCase  )


