


"""simple docstring"""




from sklearn.metrics import mean_squared_error

import datasets


__magic_name__						: Tuple    =				'\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n         and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.\n         and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and\n         Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},\n journal={Journal of Machine Learning Research},\n volume={12},\n pages={2825--2830},\n year={2011}\n}\n'

__magic_name__						: str    =				'\\nMean Squared Error(MSE) is the average of the square of difference between the predicted\nand actual values.\n'


__magic_name__						: Union[str, Any]    =				'\nArgs:\n    predictions: array-like of shape (n_samples,) or (n_samples, n_outputs)\n        Estimated target values.\n    references: array-like of shape (n_samples,) or (n_samples, n_outputs)\n        Ground truth (correct) target values.\n    sample_weight: array-like of shape (n_samples,), default=None\n        Sample weights.\n    multioutput: {"raw_values", "uniform_average"} or array-like of shape (n_outputs,), default="uniform_average"\n        Defines aggregating of multiple output values. Array-like value defines weights used to average errors.\n\n        "raw_values" : Returns a full set of errors in case of multioutput input.\n\n        "uniform_average" : Errors of all outputs are averaged with uniform weight.\n\n    squared : bool, default=True\n        If True returns MSE value, if False returns RMSE (Root Mean Squared Error) value.\n\nReturns:\n    mse : mean squared error.\nExamples:\n\n    >>> mse_metric = datasets.load_metric("mse")\n    >>> predictions = [2.5, 0.0, 2, 8]\n    >>> references = [3, -0.5, 2, 7]\n    >>> results = mse_metric.compute(predictions=predictions, references=references)\n    >>> print(results)\n    {\'mse\': 0.375}\n    >>> rmse_result = mse_metric.compute(predictions=predictions, references=references, squared=False)\n    >>> print(rmse_result)\n    {\'mse\': 0.6123724356957945}\n\n    If you\'re using multi-dimensional lists, then set the config as follows :\n\n    >>> mse_metric = datasets.load_metric("mse", "multilist")\n    >>> predictions = [[0.5, 1], [-1, 1], [7, -6]]\n    >>> references = [[0, 2], [-1, 2], [8, -5]]\n    >>> results = mse_metric.compute(predictions=predictions, references=references)\n    >>> print(results)\n    {\'mse\': 0.7083333333333334}\n    >>> results = mse_metric.compute(predictions=predictions, references=references, multioutput=\'raw_values\')\n    >>> print(results) # doctest: +NORMALIZE_WHITESPACE\n    {\'mse\': array([0.41666667, 1. ])}\n'




@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION			,		_KWARGS_DESCRIPTION  )
class 			__snake_case   (datasets.Metric  ):




							def   __a   (     self:    Tuple   ):
										return datasets.MetricInfo(
										    description=_DESCRIPTION     ,							citation=_CITATION     ,							inputs_description=_KWARGS_DESCRIPTION     ,							features=datasets.Features(self._get_feature_types()   )     ,							reference_urls=[
										        """https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html"""
										    ]     ,							)




							def   __a   (     self:    List[str]   ):







										if self.config_name == "multilist":
													return {
													    "predictions": datasets.Sequence(datasets.Value("""float"""   )   ),
													    "references": datasets.Sequence(datasets.Value("""float"""   )   ),
													}
										else:
													return {
													    "predictions": datasets.Value("""float"""   ),
													    "references": datasets.Value("""float"""   ),
													}




							def   __a   (     self:    Union[str, Any]     ,							A_:    Optional[Any]     ,							A_:    List[str]     ,							A_:    List[Any]=None     ,							A_:    int="uniform_average"     ,							A_:    Any=True   ):
										__lowerCamelCase          =      mean_squared_error(
										    __lowercase     ,							__lowercase     ,							sample_weight=__lowercase     ,							multioutput=__lowercase     ,							squared=__lowercase   )

										return {"mse": mse}








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

import math
import random
from typing import Any

class     _lowerCamelCase       :




 '''simple docstring'''


 def __init__(   self    ):

  """simple docstring"""







  __A	:		list[Any]	  =      []
  __A	:		int	  =      0
  __A	:		int	  =      0


 def 			snake_case__ (   self    ):

  """simple docstring"""







  return self.head == self.tail


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  self.data.append(__lowercase    )
  __A	:		Any	  =      self.tail + 1


 def 			snake_case__ (   self    ):

  """simple docstring"""







  __A	:		Any	  =      self.data[self.head]
  __A	:		Union[str, Any]	  =      self.head + 1
  return ret


 def 			snake_case__ (   self    ):

  """simple docstring"""







  return self.tail - self.head







 def 			snake_case__ (   self    ):

  """simple docstring"""







  print(self.data    )
  print('**************'    )
  print(self.data[self.head : self.tail]    )


class     _lowerCamelCase       :




 '''simple docstring'''


 def __init__(   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		Any	  =      data
  __A	:		MyNode | None	  =      None
  __A	:		MyNode | None	  =      None
  __A	:		int	  =      1


 def 			snake_case__ (   self    ):

  """simple docstring"""







  return self.data


 def 			snake_case__ (   self    ):

  """simple docstring"""







  return self.left


 def 			snake_case__ (   self    ):

  """simple docstring"""







  return self.right


 def 			snake_case__ (   self    ):

  """simple docstring"""







  return self.height


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		Dict	  =      data


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		int	  =      node


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		Tuple	  =      node







 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		Optional[Any]	  =      height


def       _lowercase							(					UpperCamelCase__							:       MyNode | None      ):
 if node is None:
  return 0
 return node.get_height()


def       _lowercase							(					UpperCamelCase__							:       int,					UpperCamelCase__							:       int      ):
 if a > b:
  return a
 return b


def       _lowercase							(					UpperCamelCase__							:       MyNode      ):
 print('left rotation node:',					node.get_data()      )
 __A	:		Optional[Any]	  =      node.get_left()
 assert ret is not None
 node.set_left(ret.get_right()      )
 ret.set_right(UpperCamelCase__      )
 __A	:		Tuple	  =      my_max(get_height(node.get_right()      ),					get_height(node.get_left()      )      ) + 1
 node.set_height(UpperCamelCase__      )
 __A	:		Optional[Any]	  =      my_max(get_height(ret.get_right()      ),					get_height(ret.get_left()      )      ) + 1
 ret.set_height(UpperCamelCase__      )
 return ret


def       _lowercase							(					UpperCamelCase__							:       MyNode      ):
 print('right rotation node:',					node.get_data()      )
 __A	:		Optional[Any]	  =      node.get_right()
 assert ret is not None
 node.set_right(ret.get_left()      )
 ret.set_left(UpperCamelCase__      )
 __A	:		List[str]	  =      my_max(get_height(node.get_right()      ),					get_height(node.get_left()      )      ) + 1
 node.set_height(UpperCamelCase__      )
 __A	:		Any	  =      my_max(get_height(ret.get_right()      ),					get_height(ret.get_left()      )      ) + 1
 ret.set_height(UpperCamelCase__      )
 return ret


def       _lowercase							(					UpperCamelCase__							:       MyNode      ):
 __A	:		Dict	  =      node.get_left()
 assert left_child is not None
 node.set_left(left_rotation(UpperCamelCase__      )      )
 return right_rotation(UpperCamelCase__      )


def       _lowercase							(					UpperCamelCase__							:       MyNode      ):
 __A	:		Tuple	  =      node.get_right()
 assert right_child is not None
 node.set_right(right_rotation(UpperCamelCase__      )      )
 return left_rotation(UpperCamelCase__      )


def       _lowercase							(					UpperCamelCase__							:       MyNode | None,					UpperCamelCase__							:       Any      ):
 if node is None:
  return MyNode(UpperCamelCase__      )
 if data < node.get_data():
  node.set_left(insert_node(node.get_left(),					UpperCamelCase__      )      )
  if (
      get_height(node.get_left()      ) - get_height(node.get_right()      ) == 2
  ):  # an unbalance detected
   __A	:		Union[str, Any]	  =      node.get_left()
   assert left_child is not None
   if (
       data < left_child.get_data()
   ):  # new node is the left child of the left child
    __A	:		Optional[Any]	  =      right_rotation(UpperCamelCase__      )
   else:
    __A	:		Any	  =      lr_rotation(UpperCamelCase__      )
 else:
  node.set_right(insert_node(node.get_right(),					UpperCamelCase__      )      )
  if get_height(node.get_right()      ) - get_height(node.get_left()      ) == 2:
   __A	:		Union[str, Any]	  =      node.get_right()
   assert right_child is not None
   if data < right_child.get_data():
    __A	:		int	  =      rl_rotation(UpperCamelCase__      )
   else:
    __A	:		Optional[Any]	  =      left_rotation(UpperCamelCase__      )
 __A	:		Tuple	  =      my_max(get_height(node.get_right()      ),					get_height(node.get_left()      )      ) + 1
 node.set_height(UpperCamelCase__      )
 return node


def       _lowercase							(					UpperCamelCase__							:       MyNode      ):
 while True:
  __A	:		str	  =      root.get_right()
  if right_child is None:
   break
  __A	:		Union[str, Any]	  =      right_child
 return root.get_data()


def       _lowercase							(					UpperCamelCase__							:       MyNode      ):
 while True:
  __A	:		Union[str, Any]	  =      root.get_left()
  if left_child is None:
   break
  __A	:		int	  =      left_child
 return root.get_data()


def       _lowercase							(					UpperCamelCase__							:       MyNode,					UpperCamelCase__							:       Any      ):
 __A	:		List[Any]	  =      root.get_left()
 __A	:		int	  =      root.get_right()
 if root.get_data() == data:
  if left_child is not None and right_child is not None:
   __A	:		List[Any]	  =      get_left_most(UpperCamelCase__      )
   root.set_data(UpperCamelCase__      )
   root.set_right(del_node(UpperCamelCase__,					UpperCamelCase__      )      )
  elif left_child is not None:
   __A	:		Tuple	  =      left_child
  elif right_child is not None:
   __A	:		str	  =      right_child
  else:
   return None
 elif root.get_data() > data:
  if left_child is None:
   print('No such data'      )
   return root
  else:
   root.set_left(del_node(UpperCamelCase__,					UpperCamelCase__      )      )
 else:  # root.get_data() < data
  if right_child is None:
   return root
  else:
   root.set_right(del_node(UpperCamelCase__,					UpperCamelCase__      )      )

 if get_height(UpperCamelCase__      ) - get_height(UpperCamelCase__      ) == 2:
  assert right_child is not None
  if get_height(right_child.get_right()      ) > get_height(right_child.get_left()      ):
   __A	:		List[str]	  =      left_rotation(UpperCamelCase__      )
  else:
   __A	:		Union[str, Any]	  =      rl_rotation(UpperCamelCase__      )
 elif get_height(UpperCamelCase__      ) - get_height(UpperCamelCase__      ) == -2:
  assert left_child is not None
  if get_height(left_child.get_left()      ) > get_height(left_child.get_right()      ):
   __A	:		str	  =      right_rotation(UpperCamelCase__      )
  else:
   __A	:		List[Any]	  =      lr_rotation(UpperCamelCase__      )
 __A	:		Tuple	  =      my_max(get_height(root.get_right()      ),					get_height(root.get_left()      )      ) + 1
 root.set_height(UpperCamelCase__      )
 return root

class     _lowerCamelCase       :




 '''simple docstring'''


 def __init__(   self    ):

  """simple docstring"""







  __A	:		MyNode | None	  =      None


 def 			snake_case__ (   self    ):

  """simple docstring"""







  return get_height(self.root    )


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  print('insert:' + str(__lowercase    )    )
  __A	:		Optional[int]	  =      insert_node(self.root   ,   __lowercase    )


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  print('delete:' + str(__lowercase    )    )
  if self.root is None:
   print('Tree is empty!'    )
   return
  __A	:		List[Any]	  =      del_node(self.root   ,   __lowercase    )







 def __str__(   self   ,   ):  # a level traversale, gives a more intuitive look on the tree

  """simple docstring"""







  __A	:		Union[str, Any]	  =      ''
  __A	:		Optional[Any]	  =      MyQueue()
  q.push(self.root    )
  __A	:		Tuple	  =      self.get_height()
  if layer == 0:
   return output
  __A	:		List[Any]	  =      0
  while not q.is_empty():
   __A	:		Union[str, Any]	  =      q.pop()
   __A	:		Any	  =      ' ' * int(math.pow(2   ,   layer - 1    )    )
   output += space
   if node is None:
    output += "*"
    q.push(__lowercase    )
    q.push(__lowercase    )
   else:
    output += str(node.get_data()    )
    q.push(node.get_left()    )
    q.push(node.get_right()    )
   output += space
   __A	:		Optional[int]	  =      cnt + 1
   for i in range(100    ):
    if cnt == math.pow(2   ,   __lowercase    ) - 1:
     __A	:		Optional[int]	  =      layer - 1
     if layer == 0:
      output += "\n*************************************"
      return output
     output += "\n"
     break
  output += "\n*************************************"
  return output


def       _lowercase							(					):
 import doctest

 doctest.testmod()


if __name__ == "__main__":
 _test()
 UpperCAmelCase_			:  Optional[Any]										=   AVLtree()
 UpperCAmelCase_			:  Dict										=   list(range(1_0))
 random.shuffle(lst)
 for i in lst:
  t.insert(i)
  print(str(t))
 random.shuffle(lst)
 for i in lst:
  t.del_node(i)
  print(str(t))






