



"""simple docstring"""
from __future__ import annotations

import unittest

from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
   import tensorflow as tf

   from transformers import (
       TFDebertaVaForMaskedLM,
       TFDebertaVaForQuestionAnswering,
       TFDebertaVaForSequenceClassification,
       TFDebertaVaForTokenClassification,
       TFDebertaVaModel,
   )
class 					a	:



  def __init__(						self :					List[str]       ,		lowerCAmelCase :					Any       ,		lowerCAmelCase :					Optional[Any]=13       ,		lowerCAmelCase :					Union[str, Any]=7       ,		lowerCAmelCase :					Optional[Any]=True       ,		lowerCAmelCase :					Tuple=True       ,		lowerCAmelCase :					Dict=True       ,		lowerCAmelCase :					Dict=True       ,		lowerCAmelCase :					Any=99       ,		lowerCAmelCase :					List[str]=32       ,		lowerCAmelCase :					Dict=2       ,		lowerCAmelCase :					Optional[int]=4       ,		lowerCAmelCase :					Any=37       ,		lowerCAmelCase :					List[str]="gelu"       ,		lowerCAmelCase :					List[Any]=0.1       ,		lowerCAmelCase :					Tuple=0.1       ,		lowerCAmelCase :					List[str]=512       ,		lowerCAmelCase :					List[str]=16       ,		lowerCAmelCase :					Dict=2       ,		lowerCAmelCase :					int=0.0_2       ,		lowerCAmelCase :					List[Any]=False       ,		lowerCAmelCase :					str=True       ,		lowerCAmelCase :					Tuple="None"       ,		lowerCAmelCase :					Union[str, Any]=3       ,		lowerCAmelCase :					List[str]=4       ,		lowerCAmelCase :					int=None       ,		)     ->					List[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Optional[Any]     			=parent
     SCREAMING_SNAKE_CASE_: int     			=batch_size
     SCREAMING_SNAKE_CASE_: int     			=seq_length
     SCREAMING_SNAKE_CASE_: str     			=is_training
     SCREAMING_SNAKE_CASE_: Optional[int]     			=use_input_mask
     SCREAMING_SNAKE_CASE_: List[Any]     			=use_token_type_ids
     SCREAMING_SNAKE_CASE_: str     			=use_labels
     SCREAMING_SNAKE_CASE_: List[Any]     			=vocab_size
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=hidden_size
     SCREAMING_SNAKE_CASE_: List[str]     			=num_hidden_layers
     SCREAMING_SNAKE_CASE_: Dict     			=num_attention_heads
     SCREAMING_SNAKE_CASE_: int     			=intermediate_size
     SCREAMING_SNAKE_CASE_: List[Any]     			=hidden_act
     SCREAMING_SNAKE_CASE_: Any     			=hidden_dropout_prob
     SCREAMING_SNAKE_CASE_: List[Any]     			=attention_probs_dropout_prob
     SCREAMING_SNAKE_CASE_: Optional[int]     			=max_position_embeddings
     SCREAMING_SNAKE_CASE_: Optional[int]     			=type_vocab_size
     SCREAMING_SNAKE_CASE_: List[Any]     			=type_sequence_label_size
     SCREAMING_SNAKE_CASE_: Optional[Any]     			=initializer_range
     SCREAMING_SNAKE_CASE_: Dict     			=num_labels
     SCREAMING_SNAKE_CASE_: Tuple     			=num_choices
     SCREAMING_SNAKE_CASE_: Dict     			=relative_attention
     SCREAMING_SNAKE_CASE_: str     			=position_biased_input
     SCREAMING_SNAKE_CASE_: Any     			=pos_att_type
     SCREAMING_SNAKE_CASE_: List[str]     			=scope



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					Union[str, Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Dict     			=ids_tensor([self.batch_size, self.seq_length]       ,		self.vocab_size		)

     SCREAMING_SNAKE_CASE_: List[str]     			=None
     if self.use_input_mask:
        SCREAMING_SNAKE_CASE_: Tuple     			=random_attention_mask([self.batch_size, self.seq_length]		)

     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=None
     if self.use_token_type_ids:
        SCREAMING_SNAKE_CASE_: int     			=ids_tensor([self.batch_size, self.seq_length]       ,		self.type_vocab_size		)

     SCREAMING_SNAKE_CASE_: int     			=None
     SCREAMING_SNAKE_CASE_: Dict     			=None
     SCREAMING_SNAKE_CASE_: Any     			=None
     if self.use_labels:
        SCREAMING_SNAKE_CASE_: str     			=ids_tensor([self.batch_size]       ,		self.type_sequence_label_size		)
        SCREAMING_SNAKE_CASE_: Dict     			=ids_tensor([self.batch_size, self.seq_length]       ,		self.num_labels		)

     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=DebertaVaConfig(
         vocab_size=self.vocab_size       ,		hidden_size=self.hidden_size       ,		num_hidden_layers=self.num_hidden_layers       ,		num_attention_heads=self.num_attention_heads       ,		intermediate_size=self.intermediate_size       ,		hidden_act=self.hidden_act       ,		hidden_dropout_prob=self.hidden_dropout_prob       ,		attention_probs_dropout_prob=self.attention_probs_dropout_prob       ,		max_position_embeddings=self.max_position_embeddings       ,		type_vocab_size=self.type_vocab_size       ,		relative_attention=self.relative_attention       ,		position_biased_input=self.position_biased_input       ,		initializer_range=self.initializer_range       ,		return_dict=lowerCAmelCase       ,		)

     return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels



  def 	lowerCamelCase__       (						self :					Optional[Any]       ,		lowerCAmelCase :					int       ,		lowerCAmelCase :					List[str]       ,		lowerCAmelCase :					Optional[int]       ,		lowerCAmelCase :					List[Any]       ,		lowerCAmelCase :					int       ,		lowerCAmelCase :					Optional[int]       ,		lowerCAmelCase :					Optional[Any]		)     ->					Optional[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Dict     			=TFDebertaVaModel(config=lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: Optional[Any]     			={"""input_ids""": input_ids, """attention_mask""": input_mask, """token_type_ids""": token_type_ids}

     SCREAMING_SNAKE_CASE_: List[str]     			=[input_ids, input_mask]
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=model(lowerCAmelCase		)

     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=model(lowerCAmelCase		)

     self.parent.assertEqual(result.last_hidden_state.shape       ,		(self.batch_size, self.seq_length, self.hidden_size)		)



  def 	lowerCamelCase__       (						self :					Optional[Any]       ,		lowerCAmelCase :					Dict       ,		lowerCAmelCase :					List[Any]       ,		lowerCAmelCase :					List[str]       ,		lowerCAmelCase :					Union[str, Any]       ,		lowerCAmelCase :					int       ,		lowerCAmelCase :					List[Any]       ,		lowerCAmelCase :					Optional[Any]		)     ->					Union[str, Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			=TFDebertaVaForMaskedLM(config=lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: Optional[int]     			={
         """input_ids""": input_ids,
         """attention_mask""": input_mask,
         """token_type_ids""": token_type_ids,
     }
     SCREAMING_SNAKE_CASE_: Dict     			=model(lowerCAmelCase		)
     self.parent.assertEqual(result.logits.shape       ,		(self.batch_size, self.seq_length, self.vocab_size)		)



  def 	lowerCamelCase__       (						self :					int       ,		lowerCAmelCase :					int       ,		lowerCAmelCase :					int       ,		lowerCAmelCase :					int       ,		lowerCAmelCase :					Union[str, Any]       ,		lowerCAmelCase :					Optional[Any]       ,		lowerCAmelCase :					str       ,		lowerCAmelCase :					Optional[Any]		)     ->					Optional[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			=self.num_labels
     SCREAMING_SNAKE_CASE_: int     			=TFDebertaVaForSequenceClassification(config=lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: Tuple     			={
         """input_ids""": input_ids,
         """attention_mask""": input_mask,
         """token_type_ids""": token_type_ids,
     }

     SCREAMING_SNAKE_CASE_: Optional[int]     			=model(lowerCAmelCase		)
     self.parent.assertEqual(result.logits.shape       ,		(self.batch_size, self.num_labels)		)



  def 	lowerCamelCase__       (						self :					int       ,		lowerCAmelCase :					Optional[Any]       ,		lowerCAmelCase :					Any       ,		lowerCAmelCase :					int       ,		lowerCAmelCase :					Dict       ,		lowerCAmelCase :					Dict       ,		lowerCAmelCase :					Optional[Any]       ,		lowerCAmelCase :					List[Any]		)     ->					Optional[int]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: int     			=self.num_labels
     SCREAMING_SNAKE_CASE_: Optional[int]     			=TFDebertaVaForTokenClassification(config=lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: Any     			={
         """input_ids""": input_ids,
         """attention_mask""": input_mask,
         """token_type_ids""": token_type_ids,
     }
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=model(lowerCAmelCase		)
     self.parent.assertEqual(result.logits.shape       ,		(self.batch_size, self.seq_length, self.num_labels)		)



  def 	lowerCamelCase__       (						self :					Tuple       ,		lowerCAmelCase :					Optional[Any]       ,		lowerCAmelCase :					Tuple       ,		lowerCAmelCase :					Dict       ,		lowerCAmelCase :					List[Any]       ,		lowerCAmelCase :					List[str]       ,		lowerCAmelCase :					Optional[int]       ,		lowerCAmelCase :					Optional[int]		)     ->					Optional[int]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Dict     			=TFDebertaVaForQuestionAnswering(config=lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: Tuple     			={
         """input_ids""": input_ids,
         """attention_mask""": input_mask,
         """token_type_ids""": token_type_ids,
     }

     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=model(lowerCAmelCase		)
     self.parent.assertEqual(result.start_logits.shape       ,		(self.batch_size, self.seq_length)		)
     self.parent.assertEqual(result.end_logits.shape       ,		(self.batch_size, self.seq_length)		)





  def 	lowerCamelCase__       (						self :					Union[str, Any]		)     ->					int:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[str]     			=self.prepare_config_and_inputs()
     (
         (
         SCREAMING_SNAKE_CASE_
     )			,		(
         SCREAMING_SNAKE_CASE_
     )			,		(
         SCREAMING_SNAKE_CASE_
     )			,		(
         SCREAMING_SNAKE_CASE_
     )			,		(
         SCREAMING_SNAKE_CASE_
     )			,		(
         SCREAMING_SNAKE_CASE_
     )			,		(
         SCREAMING_SNAKE_CASE_
     )			,		
     ): Optional[int]     			=config_and_inputs
     SCREAMING_SNAKE_CASE_: Tuple     			={"""input_ids""": input_ids, """token_type_ids""": token_type_ids, """attention_mask""": input_mask}
     return config, inputs_dict







@require_tf
class 					a	(  UpperCAmelCase__	,      UpperCAmelCase__	,      unittest.TestCase       ):
  UpperCamelCase	:				Optional[int]     						=					(
      (
          TFDebertaVaModel,
          TFDebertaVaForMaskedLM,
          TFDebertaVaForQuestionAnswering,
          TFDebertaVaForSequenceClassification,
          TFDebertaVaForTokenClassification,
      )
      if is_tf_available()
      else ()
  )
  UpperCamelCase	:				int     						=					(
      {
          'feature-extraction': TFDebertaVaModel,
          'fill-mask': TFDebertaVaForMaskedLM,
          'question-answering': TFDebertaVaForQuestionAnswering,
          'text-classification': TFDebertaVaForSequenceClassification,
          'token-classification': TFDebertaVaForTokenClassification,
          'zero-shot': TFDebertaVaForSequenceClassification,
      }
      if is_tf_available()
      else {}
  )

  UpperCamelCase	:				Union[str, Any]     						=					False
  UpperCamelCase	:				str     						=					False



  def 	lowerCamelCase__       (						self :					Any		)     ->					Optional[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[str]     			=TFDebertaVaModelTester(self		)
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=ConfigTester(self       ,		config_class=lowerCAmelCase       ,		hidden_size=37		)



  def 	lowerCamelCase__       (						self :					List[str]		)     ->					Optional[Any]:


     '''simple docstring'''




     self.config_tester.run_common_tests()



  def 	lowerCamelCase__       (						self :					Any		)     ->					Any:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			=self.model_tester.prepare_config_and_inputs()
     self.model_tester.create_and_check_model(*lowerCAmelCase		)



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					str:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Optional[Any]     			=self.model_tester.prepare_config_and_inputs()
     self.model_tester.create_and_check_for_masked_lm(*lowerCAmelCase		)



  def 	lowerCamelCase__       (						self :					List[Any]		)     ->					int:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: int     			=self.model_tester.prepare_config_and_inputs()
     self.model_tester.create_and_check_for_question_answering(*lowerCAmelCase		)



  def 	lowerCamelCase__       (						self :					int		)     ->					Optional[int]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[Any]     			=self.model_tester.prepare_config_and_inputs()
     self.model_tester.create_and_check_for_sequence_classification(*lowerCAmelCase		)



  def 	lowerCamelCase__       (						self :					List[str]		)     ->					int:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Any     			=self.model_tester.prepare_config_and_inputs()
     self.model_tester.create_and_check_for_token_classification(*lowerCAmelCase		)





  @slow
  def 	lowerCamelCase__       (						self :					List[str]		)     ->					Optional[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=TFDebertaVaModel.from_pretrained("""kamalkraj/deberta-v2-xlarge"""		)
     self.assertIsNotNone(lowerCAmelCase		)







@require_tf
class 					a	(  unittest.TestCase       ):



  @unittest.skip(reason="""Model not available yet"""		)
  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					Union[str, Any]:


     '''simple docstring'''




     pass





  @slow
  def 	lowerCamelCase__       (						self :					Union[str, Any]		)     ->					Union[str, Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Any     			=TFDebertaVaModel.from_pretrained("""kamalkraj/deberta-v2-xlarge"""		)
     SCREAMING_SNAKE_CASE_: Dict     			=tf.constant([[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]]		)
     SCREAMING_SNAKE_CASE_: Tuple     			=tf.constant([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]		)
     SCREAMING_SNAKE_CASE_: List[str]     			=model(lowerCAmelCase       ,		attention_mask=lowerCAmelCase		)[0]

     SCREAMING_SNAKE_CASE_: Optional[int]     			=tf.constant(
         [[[0.2_3_5_6, 0.1_9_4_8, 0.0_3_6_9], [-0.1_0_6_3, 0.3_5_8_6, -0.5_1_5_2], [-0.6_3_9_9, -0.0_2_5_9, -0.2_5_2_5]]]		)
     tf.debugging.assert_near(output[:, 1:4, 1:4]       ,		lowerCAmelCase       ,		atol=1E-4		)








"""simple docstring"""
from __future__ import annotations

import math
import random
from typing import Any
class 					a	:



  def __init__(						self :					str		)     ->					None:


     '''simple docstring'''




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



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					bool:


     '''simple docstring'''




     return self.head == self.tail



  def 	lowerCamelCase__       (						self :					Tuple       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     self.data.append(lowerCAmelCase		)
     SCREAMING_SNAKE_CASE_: List[str]     			=self.tail + 1



  def 	lowerCamelCase__       (						self :					int		)     ->					Any:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: int     			=self.data[self.head]
     SCREAMING_SNAKE_CASE_: Optional[int]     			=self.head + 1
     return ret



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					int:


     '''simple docstring'''




     return self.tail - self.head





  def 	lowerCamelCase__       (						self :					str		)     ->					None:


     '''simple docstring'''




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







class 					a	:



  def __init__(						self :					Union[str, Any]       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Dict     			=data
     SCREAMING_SNAKE_CASE_: MyNode | None     			=None
     SCREAMING_SNAKE_CASE_: MyNode | None     			=None
     SCREAMING_SNAKE_CASE_: int     			=1



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					Any:


     '''simple docstring'''




     return self.data



  def 	lowerCamelCase__       (						self :					List[Any]		)     ->					MyNode | None:


     '''simple docstring'''




     return self.left



  def 	lowerCamelCase__       (						self :					Dict		)     ->					MyNode | None:


     '''simple docstring'''




     return self.right



  def 	lowerCamelCase__       (						self :					Any		)     ->					int:


     '''simple docstring'''




     return self.height



  def 	lowerCamelCase__       (						self :					Any       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Optional[Any]     			=data



  def 	lowerCamelCase__       (						self :					Dict       ,		lowerCAmelCase :					MyNode | None		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			=node



  def 	lowerCamelCase__       (						self :					List[Any]       ,		lowerCAmelCase :					MyNode | None		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: str     			=node





  def 	lowerCamelCase__       (						self :					int       ,		lowerCAmelCase :					int		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Any     			=height







def      __magic_name__				(							lowercase ):
   if node is None:
      return 0
   return node.get_height()





def      __magic_name__				(							lowercase							,			lowercase ):
   if a > b:
      return a
   return b





def      __magic_name__				(							lowercase ):
   print("""left rotation node:"""							,			node.get_data() )
   SCREAMING_SNAKE_CASE_: List[Any]     			=node.get_left()
   assert ret is not None
   node.set_left(ret.get_right() )
   ret.set_right(lowercase )
   SCREAMING_SNAKE_CASE_: Tuple     			=my_max(get_height(node.get_right() )							,			get_height(node.get_left() ) ) + 1
   node.set_height(lowercase )
   SCREAMING_SNAKE_CASE_: int     			=my_max(get_height(ret.get_right() )							,			get_height(ret.get_left() ) ) + 1
   ret.set_height(lowercase )
   return ret





def      __magic_name__				(							lowercase ):
   print("""right rotation node:"""							,			node.get_data() )
   SCREAMING_SNAKE_CASE_: List[Any]     			=node.get_right()
   assert ret is not None
   node.set_right(ret.get_left() )
   ret.set_left(lowercase )
   SCREAMING_SNAKE_CASE_: List[Any]     			=my_max(get_height(node.get_right() )							,			get_height(node.get_left() ) ) + 1
   node.set_height(lowercase )
   SCREAMING_SNAKE_CASE_: Optional[int]     			=my_max(get_height(ret.get_right() )							,			get_height(ret.get_left() ) ) + 1
   ret.set_height(lowercase )
   return ret





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: Any     			=node.get_left()
   assert left_child is not None
   node.set_left(left_rotation(lowercase ) )
   return right_rotation(lowercase )





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: Dict     			=node.get_right()
   assert right_child is not None
   node.set_right(right_rotation(lowercase ) )
   return left_rotation(lowercase )





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





def      __magic_name__				(							lowercase ):
   while True:
      SCREAMING_SNAKE_CASE_: Dict     			=root.get_right()
      if right_child is None:
         break
      SCREAMING_SNAKE_CASE_: str     			=right_child
   return root.get_data()





def      __magic_name__				(							lowercase ):
   while True:
      SCREAMING_SNAKE_CASE_: str     			=root.get_left()
      if left_child is None:
         break
      SCREAMING_SNAKE_CASE_: Dict     			=left_child
   return root.get_data()





def      __magic_name__				(							lowercase							,			lowercase ):
   SCREAMING_SNAKE_CASE_: str     			=root.get_left()
   SCREAMING_SNAKE_CASE_: List[Any]     			=root.get_right()
   if root.get_data() == data:
      if left_child is not None and right_child is not None:
         SCREAMING_SNAKE_CASE_: Union[str, Any]     			=get_left_most(lowercase )
         root.set_data(lowercase )
         root.set_right(del_node(lowercase							,			lowercase ) )
      elif left_child is not None:
         SCREAMING_SNAKE_CASE_: Optional[int]     			=left_child
      elif right_child is not None:
         SCREAMING_SNAKE_CASE_: Any     			=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(lowercase							,			lowercase ) )
   else:  # root.get_data() < data
      if right_child is None:
         return root
      else:
         root.set_right(del_node(lowercase							,			lowercase ) )

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



  def __init__(						self :					int		)     ->					None:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: MyNode | None     			=None



  def 	lowerCamelCase__       (						self :					List[Any]		)     ->					int:


     '''simple docstring'''




     return get_height(self.root		)



  def 	lowerCamelCase__       (						self :					Optional[int]       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     print("""insert:""" + str(lowerCAmelCase		)		)
     SCREAMING_SNAKE_CASE_: Tuple     			=insert_node(self.root       ,		lowerCAmelCase		)



  def 	lowerCamelCase__       (						self :					List[Any]       ,		lowerCAmelCase :					Any		)     ->					None:


     '''simple docstring'''




     print("""delete:""" + str(lowerCAmelCase		)		)
     if self.root is None:
        print("""Tree is empty!"""		)
        return
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=del_node(self.root       ,		lowerCAmelCase		)





  def __str__(						self :					List[str]       ,		)     ->					str:  # a level traversale, gives a more intuitive look on the tree


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[Any]     			=""""""
     SCREAMING_SNAKE_CASE_: str     			=MyQueue()
     q.push(self.root		)
     SCREAMING_SNAKE_CASE_: List[str]     			=self.get_height()
     if layer == 0:
        return output
     SCREAMING_SNAKE_CASE_: int     			=0
     while not q.is_empty():
        SCREAMING_SNAKE_CASE_: int     			=q.pop()
        SCREAMING_SNAKE_CASE_: List[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
        SCREAMING_SNAKE_CASE_: List[Any]     			=cnt + 1
        for i in range(100		):
           if cnt == math.pow(2       ,		lowerCAmelCase		) - 1:
              SCREAMING_SNAKE_CASE_: int     			=layer - 1
              if layer == 0:
                 output += "\n*************************************"
                 return output
              output += "\n"
              break
     output += "\n*************************************"
     return output







def      __magic_name__				(							):
   import doctest

   doctest.testmod()


if __name__ == "__main__":
   _test()
   _UpperCAmelCase     =			AVLtree()
   _UpperCAmelCase     =			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))



