


from __future__ import annotations

import queue
class 			SCREAMING_SNAKE_CASE__  :
      def __init__(	self    :	Union[str, Any]					,							SCREAMING_SNAKE_CASE__    :	Tuple					)		->      Optional[Any]:
             a_ :		Any							=  data
             a_ :		str							=  None
             a_ :		List[Any]							=  None







def 	SCREAMING_SNAKE_CASE_						(      )     ->		TreeNode:

       """simple docstring"""

       print('\n********Press N to stop entering at any point of time********\n'    )
       a_ :		List[str]							=  input('Enter the value of the root node: '    ).strip().lower()
       a_ :		queue.Queue							=  queue.Queue()
       a_ :		List[str]							=  TreeNode(int(__A    )    )
       q.put(__A    )
       while not q.empty():
              a_ :		Tuple							=  q.get()
              a_ :		Union[str, Any]							=  F"""Enter the left node of {node_found.data}: """
              a_ :		int							=  input(__A    ).strip().lower() or 'n'
              if check == "n":
                     return tree_node
              a_ :		str							=  TreeNode(int(__A    )    )
              a_ :		Optional[Any]							=  left_node
              q.put(__A    )
              a_ :		str							=  F"""Enter the right node of {node_found.data}: """
              a_ :		Union[str, Any]							=  input(__A    ).strip().lower() or 'n'
              if check == "n":
                     return tree_node
              a_ :		Dict							=  TreeNode(int(__A    )    )
              a_ :		List[str]							=  right_node
              q.put(__A    )
       raise







def 	SCREAMING_SNAKE_CASE_						(      __A			:      TreeNode    )     ->		None:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ) or not node:
              return
       print(node.data  ,   end=','    )
       pre_order(node.left    )
       pre_order(node.right    )







def 	SCREAMING_SNAKE_CASE_						(      __A			:      TreeNode    )     ->		None:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ) or not node:
              return
       in_order(node.left    )
       print(node.data  ,   end=','    )
       in_order(node.right    )







def 	SCREAMING_SNAKE_CASE_						(      __A			:      TreeNode    )     ->		None:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ) or not node:
              return
       post_order(node.left    )
       post_order(node.right    )
       print(node.data  ,   end=','    )







def 	SCREAMING_SNAKE_CASE_						(      __A			:      TreeNode    )     ->		None:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ) or not node:
              return
       a_ :		queue.Queue							=  queue.Queue()
       q.put(__A    )
       while not q.empty():
              a_ :		Union[str, Any]							=  q.get()
              print(node_dequeued.data  ,   end=','    )
              if node_dequeued.left:
                     q.put(node_dequeued.left    )
              if node_dequeued.right:
                     q.put(node_dequeued.right    )







def 	SCREAMING_SNAKE_CASE_						(      __A			:      TreeNode    )     ->		None:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ) or not node:
              return
       a_ :		queue.Queue							=  queue.Queue()
       q.put(__A    )
       while not q.empty():
              a_ :		Any							=  []
              while not q.empty():
                     a_ :		Tuple							=  q.get()
                     print(node_dequeued.data  ,   end=','    )
                     if node_dequeued.left:
                            list_.append(node_dequeued.left    )
                     if node_dequeued.right:
                            list_.append(node_dequeued.right    )
              print()
              for node in list_:
                     q.put(__A    )







def 	SCREAMING_SNAKE_CASE_						(      __A			:      TreeNode    )     ->		None:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ) or not node:
              return
       a_ :		list[TreeNode]							=  []
       a_ :		Tuple							=  node
       while n or stack:
              while n:  # start from root node, find its left child
                     print(n.data  ,   end=','    )
                     stack.append(__A    )
                     a_ :		Dict							=  n.left
              # end of while means current node doesn't have left child
              a_ :		int							=  stack.pop()
              # start to traverse its right child
              a_ :		Dict							=  n.right







def 	SCREAMING_SNAKE_CASE_						(      __A			:      TreeNode    )     ->		None:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ) or not node:
              return
       a_ :		list[TreeNode]							=  []
       a_ :		Optional[int]							=  node
       while n or stack:
              while n:
                     stack.append(__A    )
                     a_ :		int							=  n.left
              a_ :		str							=  stack.pop()
              print(n.data  ,   end=','    )
              a_ :		List[str]							=  n.right







def 	SCREAMING_SNAKE_CASE_						(      __A			:      TreeNode    )     ->		None:

       """simple docstring"""

       if not isinstance(__A  ,   __A    ) or not node:
              return
       a_							,		a_ :		int							=  [], []
       a_ :		List[Any]							=  node
       stacka.append(__A    )
       while stacka:  # to find the reversed order of post order, store it in stack2
              a_ :		Optional[int]							=  stacka.pop()
              if n.left:
                     stacka.append(n.left    )
              if n.right:
                     stacka.append(n.right    )
              stacka.append(__A    )
       while stacka:  # pop up from stack2 will be the post order
              print(stacka.pop().data  ,   end=','    )







def 	SCREAMING_SNAKE_CASE_						(      __A			:      str = ""  ,   __A			:      Dict=50  ,   __A			:      Optional[Any]="*"    )     ->		str:

       """simple docstring"""

       if not s:
              return "\n" + width * char
       a_							,		a_ :		List[Any]							=  divmod(width - len(__A    ) - 2  ,   2    )
       return F"""{left * char} {s} {(left + extra) * char}"""


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   print(prompt('Binary Tree Traversals'))

   UpperCAmelCase_				:			TreeNode   =	build_tree()
   print(prompt('Pre Order Traversal'))
   pre_order(node)
   print(prompt() + '\n')

   print(prompt('In Order Traversal'))
   in_order(node)
   print(prompt() + '\n')

   print(prompt('Post Order Traversal'))
   post_order(node)
   print(prompt() + '\n')

   print(prompt('Level Order Traversal'))
   level_order(node)
   print(prompt() + '\n')

   print(prompt('Actual Level Order Traversal'))
   level_order_actual(node)
   print('*' * 50 + '\n')

   print(prompt('Pre Order Traversal - Iteration Version'))
   pre_order_iter(node)
   print(prompt() + '\n')

   print(prompt('In Order Traversal - Iteration Version'))
   in_order_iter(node)
   print(prompt() + '\n')

   print(prompt('Post Order Traversal - Iteration Version'))
   post_order_iter(node)
   print(prompt())






from typing import TYPE_CHECKING

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


UpperCAmelCase_				:			Any   =	{
    'configuration_mobilebert': [
        'MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileBertConfig',
        'MobileBertOnnxConfig',
    ],
    'tokenization_mobilebert': ['MobileBertTokenizer'],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase_				:			Union[str, Any]   =	['MobileBertTokenizerFast']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase_				:			List[str]   =	[
       'MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'MobileBertForMaskedLM',
       'MobileBertForMultipleChoice',
       'MobileBertForNextSentencePrediction',
       'MobileBertForPreTraining',
       'MobileBertForQuestionAnswering',
       'MobileBertForSequenceClassification',
       'MobileBertForTokenClassification',
       'MobileBertLayer',
       'MobileBertModel',
       'MobileBertPreTrainedModel',
       'load_tf_weights_in_mobilebert',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase_				:			Tuple   =	[
       'TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TFMobileBertForMaskedLM',
       'TFMobileBertForMultipleChoice',
       'TFMobileBertForNextSentencePrediction',
       'TFMobileBertForPreTraining',
       'TFMobileBertForQuestionAnswering',
       'TFMobileBertForSequenceClassification',
       'TFMobileBertForTokenClassification',
       'TFMobileBertMainLayer',
       'TFMobileBertModel',
       'TFMobileBertPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_mobilebert import (
       MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       MobileBertConfig,
       MobileBertOnnxConfig,
   )
   from .tokenization_mobilebert import MobileBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_mobilebert_fast import MobileBertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mobilebert import (
          MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          MobileBertForMaskedLM,
          MobileBertForMultipleChoice,
          MobileBertForNextSentencePrediction,
          MobileBertForPreTraining,
          MobileBertForQuestionAnswering,
          MobileBertForSequenceClassification,
          MobileBertForTokenClassification,
          MobileBertLayer,
          MobileBertModel,
          MobileBertPreTrainedModel,
          load_tf_weights_in_mobilebert,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_mobilebert import (
          TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFMobileBertForMaskedLM,
          TFMobileBertForMultipleChoice,
          TFMobileBertForNextSentencePrediction,
          TFMobileBertForPreTraining,
          TFMobileBertForQuestionAnswering,
          TFMobileBertForSequenceClassification,
          TFMobileBertForTokenClassification,
          TFMobileBertMainLayer,
          TFMobileBertModel,
          TFMobileBertPreTrainedModel,
      )

else:
   import sys

   UpperCAmelCase_				:			Tuple   =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


