






'''simple docstring'''
from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any






@dataclass
class        __SCREAMING_SNAKE_CASE    :
 snake_case_												=							42
 snake_case_												=							None
 snake_case_												=							None





def 	_a(					):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			List[str]													=Node(1							)
      SCREAMING_SNAKE_CASE__       :			int													=Node(2							)
      SCREAMING_SNAKE_CASE__       :			Tuple													=Node(3							)
      SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=Node(4							)
      SCREAMING_SNAKE_CASE__       :			int													=Node(5							)
      return tree





def 	_a(					UpperCamelCase__			:  Node | None							):




      '''simple docstring'''






      return [root.data, *preorder(root.left							), *preorder(root.right							)] if root else []





def 	_a(					UpperCamelCase__			:  Node | None							):




      '''simple docstring'''






      return postorder(root.left							) + postorder(root.right							) + [root.data] if root else []





def 	_a(					UpperCamelCase__			:  Node | None							):




      '''simple docstring'''






      return [*inorder(root.left							), root.data, *inorder(root.right							)] if root else []





def 	_a(					UpperCamelCase__			:  Node | None							):




      '''simple docstring'''






      return (max(height(root.left							),		height(root.right							)							) + 1) if root else 0





def 	_a(					UpperCamelCase__			:  Node | None							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			list[Any]													=[]

      if root is None:
            return output

      SCREAMING_SNAKE_CASE__       :			Optional[Any]													=deque([root]							)

      while process_queue:
            SCREAMING_SNAKE_CASE__       :			Any													=process_queue.popleft()
            output.append(node.data							)

            if node.left:
                  process_queue.append(node.left							)
            if node.right:
                  process_queue.append(node.right							)
      return output





def 	_a(					UpperCamelCase__			:  Node | None,		UpperCamelCase__			:  int							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			list[Any]													=[]

      def populate_output(UpperCamelCase__			:  Node | None,		UpperCamelCase__			:  int							) -> None:
            if not root:
                  return
            if level == 1:
                  output.append(root.data							)
            elif level > 1:
                  populate_output(root.left,		level - 1							)
                  populate_output(root.right,		level - 1							)

      populate_output(UpperCamelCase__,		UpperCamelCase__							)
      return output





def 	_a(					UpperCamelCase__			:  Node | None,		UpperCamelCase__			:  int							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			list[Any]													=[]

      def populate_output(UpperCamelCase__			:  Node | None,		UpperCamelCase__			:  int							) -> None:
            if root is None:
                  return
            if level == 1:
                  output.append(root.data							)
            elif level > 1:
                  populate_output(root.right,		level - 1							)
                  populate_output(root.left,		level - 1							)

      populate_output(UpperCamelCase__,		UpperCamelCase__							)
      return output





def 	_a(					UpperCamelCase__			:  Node | None							):




      '''simple docstring'''






      if root is None:
            return []

      SCREAMING_SNAKE_CASE__       :			list[Sequence[Node | None]]													=[]

      SCREAMING_SNAKE_CASE__       :			int													=0
      SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=height(UpperCamelCase__							)

      for h in range(1,		height_tree + 1							):
            if not flag:
                  output.append(get_nodes_from_left_to_right(UpperCamelCase__,		UpperCamelCase__							)							)
                  SCREAMING_SNAKE_CASE__       :			int													=1
            else:
                  output.append(get_nodes_from_right_to_left(UpperCamelCase__,		UpperCamelCase__							)							)
                  SCREAMING_SNAKE_CASE__       :			Optional[Any]													=0

      return output





def 	_a(					):  # Main function for testing.




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			List[str]													=make_tree()
      print(f"In-order Traversal: {inorder(UpperCamelCase__							)}"							)
      print(f"Pre-order Traversal: {preorder(UpperCamelCase__							)}"							)
      print(f"Post-order Traversal: {postorder(UpperCamelCase__							)}",		'''\n'''							)

      print(f"Height of Tree: {height(UpperCamelCase__							)}",		'''\n'''							)

      print('''Complete Level Order Traversal: '''							)
      print(level_order(UpperCamelCase__							),		'''\n'''							)

      print('''Level-wise order Traversal: '''							)

      for level in range(1,		height(UpperCamelCase__							) + 1							):
            print(f"Level {level}:",		get_nodes_from_left_to_right(UpperCamelCase__,		level=UpperCamelCase__							)							)

      print('''\nZigZag order Traversal: '''							)
      print(zigzag(UpperCamelCase__							)							)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()







'''simple docstring'''
from typing import TYPE_CHECKING

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


a_					=	{
    'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertConfig'],
    'tokenization_lxmert': ['LxmertTokenizer'],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					=	['LxmertTokenizerFast']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					=	[
      'LxmertEncoder',
      'LxmertForPreTraining',
      'LxmertForQuestionAnswering',
      'LxmertModel',
      'LxmertPreTrainedModel',
      'LxmertVisualFeatureEncoder',
      'LxmertXLayer',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					=	[
      'TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TFLxmertForPreTraining',
      'TFLxmertMainLayer',
      'TFLxmertModel',
      'TFLxmertPreTrainedModel',
      'TFLxmertVisualFeatureEncoder',
  ]


if TYPE_CHECKING:
  from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
  from .tokenization_lxmert import LxmertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_lxmert_fast import LxmertTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_lxmert import (
        LxmertEncoder,
        LxmertForPreTraining,
        LxmertForQuestionAnswering,
        LxmertModel,
        LxmertPreTrainedModel,
        LxmertVisualFeatureEncoder,
        LxmertXLayer,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_lxmert import (
        TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFLxmertForPreTraining,
        TFLxmertMainLayer,
        TFLxmertModel,
        TFLxmertPreTrainedModel,
        TFLxmertVisualFeatureEncoder,
    )

else:
  import sys

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