





"""simple docstring"""





from __future__ import annotations

from random import random




class 							snake_case							:

      '''simple docstring'''



      def __init__(							self       :      Dict						,				__lowercase       :      int | None = None ):


        '''simple docstring'''




        __UpperCAmelCase    :						Union[str, Any]       =						value
        __UpperCAmelCase    :						int       =						random()
        __UpperCAmelCase    :						Node | None       =						None
        __UpperCAmelCase    :						Node | None       =						None

      def __repr__(							self       :      Optional[int] ):


        '''simple docstring'''




        from pprint import pformat

        if self.left is None and self.right is None:
          return f'''\'{self.value}: {self.prior:.5}\''''
        else:
          return pformat(
              {f'''{self.value}: {self.prior:.5}''': (self.left, self.right)}						,				indent=1 )







      def __str__(							self       :      Any ):


        '''simple docstring'''




        __UpperCAmelCase    :						Tuple       =						str(self.value ) + ''' '''
        __UpperCAmelCase    :						str       =						str(self.left or '''''' )
        __UpperCAmelCase    :						Dict       =						str(self.right or '''''' )
        return value + left + right


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  )						->tuple[Node | None, Node | None]:





  """simple docstring"""


  if root is None:  # None tree is split into 2 Nones
    return None, None
  elif root.value is None:
    return None, None
  else:
    if value < root.value:
      __UpperCAmelCase       ,     __UpperCAmelCase    :						List[Any]       =						split(root.left  ,			UpperCAmelCase_  )
      return left, root
    else:
      __UpperCAmelCase       ,     __UpperCAmelCase    :						str       =						split(root.right  ,			UpperCAmelCase_  )
      return root, right


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  )						->Node | None:





  """simple docstring"""


  if (not left) or (not right):  # If one node is None, return the other
    return left or right
  elif left.prior < right.prior:
    __UpperCAmelCase    :						Dict       =						merge(left.right  ,			UpperCAmelCase_  )
    return left
  else:
    __UpperCAmelCase    :						str       =						merge(UpperCAmelCase_  ,			right.left  )
    return right


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  )						->Node | None:





  """simple docstring"""


  __UpperCAmelCase    :						Dict       =						Node(UpperCAmelCase_  )
  __UpperCAmelCase       ,     __UpperCAmelCase    :						int       =						split(UpperCAmelCase_  ,			UpperCAmelCase_  )
  return merge(merge(UpperCAmelCase_  ,			UpperCAmelCase_  )  ,			UpperCAmelCase_  )


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  )						->Node | None:





  """simple docstring"""


  __UpperCAmelCase       ,     __UpperCAmelCase    :						Any       =						split(UpperCAmelCase_  ,			value - 1  )
  __UpperCAmelCase       ,     __UpperCAmelCase    :						List[str]       =						split(UpperCAmelCase_  ,			UpperCAmelCase_  )
  return merge(UpperCAmelCase_  ,			UpperCAmelCase_  )


def       lowerCamelCase_       (   UpperCAmelCase_  )						->None:





  """simple docstring"""


  if not root:  # None
    return
  else:
    inorder(root.left  )
    print(root.value  ,			end=''','''  )
    inorder(root.right  )


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  )						->Node | None:





  """simple docstring"""


  for arg in args.split():
    if arg[0] == "+":
      __UpperCAmelCase    :						Optional[int]       =						insert(UpperCAmelCase_  ,			int(arg[1:]  )  )

    elif arg[0] == "-":
      __UpperCAmelCase    :						List[str]       =						erase(UpperCAmelCase_  ,			int(arg[1:]  )  )

    else:
      print('''Unknown command'''  )

  return root


def       lowerCamelCase_       (   )						->None:





  """simple docstring"""


  __UpperCAmelCase    :						Any       =						None
  print(
      '''enter numbers to create a tree, + value to add value into treap, '''
      '''- value to erase all nodes with value. \'q\' to quit. '''  )

  __UpperCAmelCase    :						List[Any]       =						input()
  while args != "q":
    __UpperCAmelCase    :						List[Any]       =						interact_treap(UpperCAmelCase_  ,			UpperCAmelCase_  )
    print(UpperCAmelCase_  )
    __UpperCAmelCase    :						Optional[Any]       =						input()

  print('''good by!'''  )


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


lowercase__				:Tuple				   =       {
    'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
    'tokenization_xlm': ['XLMTokenizer'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase__				:Optional[Any]				   =       [
      'XLM_PRETRAINED_MODEL_ARCHIVE_LIST',
      'XLMForMultipleChoice',
      'XLMForQuestionAnswering',
      'XLMForQuestionAnsweringSimple',
      'XLMForSequenceClassification',
      'XLMForTokenClassification',
      'XLMModel',
      'XLMPreTrainedModel',
      'XLMWithLMHeadModel',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase__				:List[Any]				   =       [
      'TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TFXLMForMultipleChoice',
      'TFXLMForQuestionAnsweringSimple',
      'TFXLMForSequenceClassification',
      'TFXLMForTokenClassification',
      'TFXLMMainLayer',
      'TFXLMModel',
      'TFXLMPreTrainedModel',
      'TFXLMWithLMHeadModel',
  ]


if TYPE_CHECKING:
  from .configuration_xlm import XLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMConfig, XLMOnnxConfig
  from .tokenization_xlm import XLMTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_xlm import (
        XLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        XLMForMultipleChoice,
        XLMForQuestionAnswering,
        XLMForQuestionAnsweringSimple,
        XLMForSequenceClassification,
        XLMForTokenClassification,
        XLMModel,
        XLMPreTrainedModel,
        XLMWithLMHeadModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_xlm import (
        TF_XLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFXLMForMultipleChoice,
        TFXLMForQuestionAnsweringSimple,
        TFXLMForSequenceClassification,
        TFXLMForTokenClassification,
        TFXLMMainLayer,
        TFXLMModel,
        TFXLMPreTrainedModel,
        TFXLMWithLMHeadModel,
    )

else:
  import sys

  lowercase__				:List[Any]				   =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)