"""simple docstring"""




from __future__ import annotations

import math
import random
from typing import Any
class 						__A							:






     def __init__(		self  ):
       _lowerCAmelCase						:	List[Any]        =					[]
       _lowerCAmelCase						:	List[Any]        =					0
       _lowerCAmelCase						:	Dict        =					0






     def    __A  (		self  ):
       return self.head == self.tail






     def    __A  (		self    ,					a__  ):
       self.data.append(_lowerCAmelCase  )
       _lowerCAmelCase						:	Optional[int]        =					self.tail + 1






     def    __A  (		self  ):
       _lowerCAmelCase						:	str        =					self.data[self.head]
       _lowerCAmelCase						:	Tuple        =					self.head + 1
       return ret






     def    __A  (		self  ):
       return self.tail - self.head






     def    __A  (		self  ):
       print(self.data  )
       print("""**************"""  )
       print(self.data[self.head : self.tail]  )







class 						__A							:






     def __init__(		self    ,					a__  ):
       _lowerCAmelCase						:	int        =					data
       _lowerCAmelCase						:	List[Any]        =					None
       _lowerCAmelCase						:	List[str]        =					None
       _lowerCAmelCase						:	Tuple        =					1






     def    __A  (		self  ):
       return self.data






     def    __A  (		self  ):
       return self.left






     def    __A  (		self  ):
       return self.right






     def    __A  (		self  ):
       return self.height






     def    __A  (		self    ,					a__  ):
       _lowerCAmelCase						:	List[str]        =					data






     def    __A  (		self    ,					a__  ):
       _lowerCAmelCase						:	Optional[Any]        =					node






     def    __A  (		self    ,					a__  ):
       _lowerCAmelCase						:	Dict        =					node






     def    __A  (		self    ,					a__  ):
       _lowerCAmelCase						:	Dict        =					height







def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	int     )	->				Optional[int]:



  if node is None:
    return 0
  return node.get_height()





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	int      ,_lowerCamelCase						:	str     )	->				List[Any]:



  if a > b:
    return a
  return b





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	Union[str, Any]     )	->				Any:
  print("""left rotation node:"""      ,node.get_data()     )
  _lowerCAmelCase						:	Tuple        =					node.get_left()
  assert ret is not None
  node.set_left(ret.get_right()     )
  ret.set_right(_lowerCAmelCase     )
  _lowerCAmelCase						:	Tuple        =					my_max(get_height(node.get_right()     )      ,get_height(node.get_left()     )     ) + 1
  node.set_height(_lowerCAmelCase     )
  _lowerCAmelCase						:	int        =					my_max(get_height(ret.get_right()     )      ,get_height(ret.get_left()     )     ) + 1
  ret.set_height(_lowerCAmelCase     )
  return ret





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	List[Any]     )	->				Dict:
  print("""right rotation node:"""      ,node.get_data()     )
  _lowerCAmelCase						:	Tuple        =					node.get_right()
  assert ret is not None
  node.set_right(ret.get_left()     )
  ret.set_left(_lowerCAmelCase     )
  _lowerCAmelCase						:	int        =					my_max(get_height(node.get_right()     )      ,get_height(node.get_left()     )     ) + 1
  node.set_height(_lowerCAmelCase     )
  _lowerCAmelCase						:	Optional[int]        =					my_max(get_height(ret.get_right()     )      ,get_height(ret.get_left()     )     ) + 1
  ret.set_height(_lowerCAmelCase     )
  return ret





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	Optional[int]     )	->				str:
  _lowerCAmelCase						:	Union[str, Any]        =					node.get_left()
  assert left_child is not None
  node.set_left(left_rotation(_lowerCAmelCase     )     )
  return right_rotation(_lowerCAmelCase     )





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	List[str]     )	->				Optional[int]:
  _lowerCAmelCase						:	int        =					node.get_right()
  assert right_child is not None
  node.set_right(right_rotation(_lowerCAmelCase     )     )
  return left_rotation(_lowerCAmelCase     )





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	List[str]      ,_lowerCamelCase						:	int     )	->				Tuple:



  if node is None:
    return MyNode(_lowerCAmelCase     )
  if data < node.get_data():
    node.set_left(insert_node(node.get_left()      ,_lowerCAmelCase     )     )
    if (
        get_height(node.get_left()     ) - get_height(node.get_right()     ) == 2
    ):  # an unbalance detected
      _lowerCAmelCase						:	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
        _lowerCAmelCase						:	List[str]        =					right_rotation(_lowerCAmelCase     )
      else:
        _lowerCAmelCase						:	List[Any]        =					lr_rotation(_lowerCAmelCase     )
  else:
    node.set_right(insert_node(node.get_right()      ,_lowerCAmelCase     )     )
    if get_height(node.get_right()     ) - get_height(node.get_left()     ) == 2:
      _lowerCAmelCase						:	List[str]        =					node.get_right()
      assert right_child is not None
      if data < right_child.get_data():
        _lowerCAmelCase						:	Union[str, Any]        =					rl_rotation(_lowerCAmelCase     )
      else:
        _lowerCAmelCase						:	Dict        =					left_rotation(_lowerCAmelCase     )
  _lowerCAmelCase						:	Optional[int]        =					my_max(get_height(node.get_right()     )      ,get_height(node.get_left()     )     ) + 1
  node.set_height(_lowerCAmelCase     )
  return node





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	Any     )	->				int:



  while True:
    _lowerCAmelCase						:	Optional[int]        =					root.get_right()
    if right_child is None:
      break
    _lowerCAmelCase						:	int        =					right_child
  return root.get_data()





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	List[Any]     )	->				Tuple:



  while True:
    _lowerCAmelCase						:	List[str]        =					root.get_left()
    if left_child is None:
      break
    _lowerCAmelCase						:	Dict        =					left_child
  return root.get_data()





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	Union[str, Any]      ,_lowerCamelCase						:	Optional[Any]     )	->				Tuple:
  _lowerCAmelCase						:	List[str]        =					root.get_left()
  _lowerCAmelCase						:	Union[str, Any]        =					root.get_right()
  if root.get_data() == data:
    if left_child is not None and right_child is not None:
      _lowerCAmelCase						:	Dict        =					get_left_most(_lowerCAmelCase     )
      root.set_data(_lowerCAmelCase     )
      root.set_right(del_node(_lowerCAmelCase      ,_lowerCAmelCase     )     )
    elif left_child is not None:
      _lowerCAmelCase						:	Union[str, Any]        =					left_child
    elif right_child is not None:
      _lowerCAmelCase						:	int        =					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(_lowerCAmelCase      ,_lowerCAmelCase     )     )
  else:  # root.get_data() < data
    if right_child is None:
      return root
    else:
      root.set_right(del_node(_lowerCAmelCase      ,_lowerCAmelCase     )     )

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






     def __init__(		self  ):
       _lowerCAmelCase						:	Any        =					None






     def    __A  (		self  ):
       return get_height(self.root  )






     def    __A  (		self    ,					a__  ):
       print("""insert:""" + str(_lowerCAmelCase  )  )
       _lowerCAmelCase						:	str        =					insert_node(self.root    ,					_lowerCAmelCase  )






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






     def __str__(		self    ,					):  # a level traversale, gives a more intuitive look on the tree
       _lowerCAmelCase						:	Dict        =					""""""
       _lowerCAmelCase						:	List[Any]        =					MyQueue()
       q.push(self.root  )
       _lowerCAmelCase						:	Optional[int]        =					self.get_height()
       if layer == 0:
         return output
       _lowerCAmelCase						:	Union[str, Any]        =					0
       while not q.is_empty():
         _lowerCAmelCase						:	Optional[Any]        =					q.pop()
         _lowerCAmelCase						:	Optional[Any]        =					""" """ * int(math.pow(2    ,					layer - 1  )  )
         output += space
         if node is None:
           output += "*"
           q.push(_lowerCAmelCase  )
           q.push(_lowerCAmelCase  )
         else:
           output += str(node.get_data()  )
           q.push(node.get_left()  )
           q.push(node.get_right()  )
         output += space
         _lowerCAmelCase						:	List[Any]        =					cnt + 1
         for i in range(100  ):
           if cnt == math.pow(2    ,					_lowerCAmelCase  ) - 1:
             _lowerCAmelCase						:	Optional[Any]        =					layer - 1
             if layer == 0:
               output += "\n*************************************"
               return output
             output += "\n"
             break
       output += "\n*************************************"
       return output







def 							SCREAMING_SNAKE_CASE					(      )	->				List[Any]:
  import doctest

  doctest.testmod()


if __name__ == "__main__":
     _test()
     _a				:		Dict	   =       AVLtree()
     _a				:		int	   =       list(range(10))
     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))





"""simple docstring"""




from dataclasses import dataclass
from typing import Optional, Tuple

import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class 						__A							(			SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Optional[torch.FloatTensor]		 =		None
     _UpperCamelCase							:      torch.FloatTensor		 =		None
     _UpperCamelCase							:      Optional[Tuple[torch.FloatTensor]]		 =		None
     _UpperCamelCase							:      Optional[Tuple[torch.FloatTensor]]		 =		None







class 						__A							(			SCREAMING_SNAKE_CASE_		):






     def __init__(		self    ,					a__=1    ,					a__=0    ,					a__=2    ,					a__=512    ,					a__="cls"    ,					a__=False    ,					a__=True    ,					**a__    ,					):
       super().__init__(pad_token_id=a__    ,					bos_token_id=a__    ,					eos_token_id=a__    ,					**a__  )
       _lowerCAmelCase						:	Optional[Any]        =					project_dim
       _lowerCAmelCase						:	List[str]        =					pooler_fn
       _lowerCAmelCase						:	Any        =					learn_encoder
       _lowerCAmelCase						:	Optional[int]        =					use_attention_mask







class 						__A							(			SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Optional[int]		 =		[R"pooler", R"logit_scale"]
     _UpperCamelCase							:      List[Any]		 =		[R"position_ids", R"predictions.decoder.bias"]
     _UpperCamelCase							:      List[Any]		 =		"roberta"
     _UpperCamelCase							:      Optional[int]		 =		RobertaSeriesConfig






     def __init__(		self    ,					a__  ):
       super().__init__(a__  )
       _lowerCAmelCase						:	str        =					XLMRobertaModel(a__  )
       _lowerCAmelCase						:	Optional[Any]        =					nn.Linear(config.hidden_size    ,					config.project_dim  )
       _lowerCAmelCase						:	List[Any]        =					getattr(a__    ,					"""has_pre_transformation"""    ,					a__  )
       if self.has_pre_transformation:
         _lowerCAmelCase						:	List[str]        =					nn.Linear(config.hidden_size    ,					config.project_dim  )
         _lowerCAmelCase						:	Optional[int]        =					nn.LayerNorm(config.hidden_size    ,					eps=config.layer_norm_eps  )
       self.post_init()






     def    __A  (		self    ,					a__ = None    ,					a__ = None    ,					a__ = None    ,					a__ = None    ,					a__ = None    ,					a__ = None    ,					a__ = None    ,					a__ = None    ,					a__ = None    ,					a__ = None    ,					a__ = None    ,					):
       _lowerCAmelCase						:	List[str]        =					return_dict if return_dict is not None else self.config.use_return_dict

       _lowerCAmelCase						:	Optional[int]        =					self.base_model(
           input_ids=a__    ,					attention_mask=a__    ,					token_type_ids=a__    ,					position_ids=a__    ,					head_mask=a__    ,					inputs_embeds=a__    ,					encoder_hidden_states=a__    ,					encoder_attention_mask=a__    ,					output_attentions=a__    ,					output_hidden_states=True if self.has_pre_transformation else output_hidden_states    ,					return_dict=a__    ,					)

       if self.has_pre_transformation:
         _lowerCAmelCase						:	Optional[Any]        =					outputs["""hidden_states"""][-2]
         _lowerCAmelCase						:	Optional[Any]        =					self.pre_LN(a__  )
         _lowerCAmelCase						:	int        =					self.transformation_pre(a__  )

         return TransformationModelOutput(
             projection_state=a__    ,					last_hidden_state=outputs.last_hidden_state    ,					hidden_states=outputs.hidden_states    ,					attentions=outputs.attentions    ,					)
       else:
         _lowerCAmelCase						:	Union[str, Any]        =					self.transformation(outputs.last_hidden_state  )
         return TransformationModelOutput(
             projection_state=a__    ,					last_hidden_state=outputs.last_hidden_state    ,					hidden_states=outputs.hidden_states    ,					attentions=outputs.attentions    ,					)




