'''simple docstring'''





from __future__ import annotations

import math
import random
from typing import Any




class 		SCREAMING_SNAKE_CASE  :







				'''simple docstring'''





				def __init__(    self       :    Tuple       )				->None:


										'''simple docstring'''




										_UpperCamelCase      :      int       =    []
										_UpperCamelCase      :      Any       =    0
										_UpperCamelCase      :      Union[str, Any]       =    0





				def 			snake_case__					(    self       :    str       )				->bool:


										'''simple docstring'''




										return self.head == self.tail





				def 			snake_case__					(    self       :    Any							,		lowercase__       :    Optional[int]       )				->None:


										'''simple docstring'''




										self.data.append(_UpperCAmelCase       )
										_UpperCamelCase      :      List[Any]       =    self.tail + 1





				def 			snake_case__					(    self       :    Any       )				->Any:


										'''simple docstring'''




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





				def 			snake_case__					(    self       :    int       )				->int:


										'''simple docstring'''




										return self.tail - self.head







				def 			snake_case__					(    self       :    Optional[int]       )				->None:


										'''simple docstring'''




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





class 		SCREAMING_SNAKE_CASE  :







				'''simple docstring'''





				def __init__(    self       :    Dict							,		lowercase__       :    List[str]       )				->None:


										'''simple docstring'''




										_UpperCamelCase      :      Dict       =    data
										_UpperCamelCase      :      Union[str, Any]       =    None
										_UpperCamelCase      :      int       =    None
										_UpperCamelCase      :      int       =    1





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


										'''simple docstring'''




										return self.data





				def 			snake_case__					(    self       :    Optional[int]       )				->MyNode | None:


										'''simple docstring'''




										return self.left





				def 			snake_case__					(    self       :    Optional[Any]       )				->MyNode | None:


										'''simple docstring'''




										return self.right





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


										'''simple docstring'''




										return self.height





				def 			snake_case__					(    self       :    List[Any]							,		lowercase__       :    Dict       )				->None:


										'''simple docstring'''




										_UpperCamelCase      :      Any       =    data





				def 			snake_case__					(    self       :    Dict							,		lowercase__       :    int       )				->None:


										'''simple docstring'''




										_UpperCamelCase      :      Tuple       =    node





				def 			snake_case__					(    self       :    List[Any]							,		lowercase__       :    List[Any]       )				->None:


										'''simple docstring'''




										_UpperCamelCase      :      Union[str, Any]       =    node







				def 			snake_case__					(    self       :    Tuple							,		lowercase__       :    Dict       )				->None:


										'''simple docstring'''




										_UpperCamelCase      :      int       =    height





def     __A				(  UpperCAmelCase       )  ->      Optional[int]:




						'''simple docstring'''
						if node is None:
												return 0
						return node.get_height()
def     __A				(  UpperCAmelCase  ,UpperCAmelCase       )  ->      str:




						'''simple docstring'''
						if a > b:
												return a
						return b
def     __A				(  UpperCAmelCase       )  ->      str:




						'''simple docstring'''
						print("left rotation node:"  ,node.get_data()       )
						_UpperCamelCase      :      Union[str, Any]       =    node.get_left()
						assert ret is not None
						node.set_left(ret.get_right()       )
						ret.set_right(__lowercase       )
						_UpperCamelCase      :      str       =    my_max(get_height(node.get_right()       )  ,get_height(node.get_left()       )       ) + 1
						node.set_height(__lowercase       )
						_UpperCamelCase      :      Any       =    my_max(get_height(ret.get_right()       )  ,get_height(ret.get_left()       )       ) + 1
						ret.set_height(__lowercase       )
						return ret
def     __A				(  UpperCAmelCase       )  ->      str:




						'''simple docstring'''
						print("right rotation node:"  ,node.get_data()       )
						_UpperCamelCase      :      Union[str, Any]       =    node.get_right()
						assert ret is not None
						node.set_right(ret.get_left()       )
						ret.set_left(__lowercase       )
						_UpperCamelCase      :      Tuple       =    my_max(get_height(node.get_right()       )  ,get_height(node.get_left()       )       ) + 1
						node.set_height(__lowercase       )
						_UpperCamelCase      :      Union[str, Any]       =    my_max(get_height(ret.get_right()       )  ,get_height(ret.get_left()       )       ) + 1
						ret.set_height(__lowercase       )
						return ret
def     __A				(  UpperCAmelCase       )  ->      Optional[int]:




						'''simple docstring'''
						_UpperCamelCase      :      str       =    node.get_left()
						assert left_child is not None
						node.set_left(left_rotation(__lowercase       )       )
						return right_rotation(__lowercase       )
def     __A				(  UpperCAmelCase       )  ->      str:




						'''simple docstring'''
						_UpperCamelCase      :      Optional[Any]       =    node.get_right()
						assert right_child is not None
						node.set_right(right_rotation(__lowercase       )       )
						return left_rotation(__lowercase       )
def     __A				(  UpperCAmelCase  ,UpperCAmelCase       )  ->      Dict:




						'''simple docstring'''
						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
																		_UpperCamelCase      :      List[str]       =    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
																								_UpperCamelCase      :      Union[str, Any]       =    right_rotation(__lowercase       )
																		else:
																								_UpperCamelCase      :      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:
																		_UpperCamelCase      :      str       =    node.get_right()
																		assert right_child is not None
																		if data < right_child.get_data():
																								_UpperCamelCase      :      Any       =    rl_rotation(__lowercase       )
																		else:
																								_UpperCamelCase      :      Optional[int]       =    left_rotation(__lowercase       )
						_UpperCamelCase      :      int       =    my_max(get_height(node.get_right()       )  ,get_height(node.get_left()       )       ) + 1
						node.set_height(__lowercase       )
						return node
def     __A				(  UpperCAmelCase       )  ->      Optional[Any]:




						'''simple docstring'''
						while True:
												_UpperCamelCase      :      Union[str, Any]       =    root.get_right()
												if right_child is None:
																		break
												_UpperCamelCase      :      List[Any]       =    right_child
						return root.get_data()
def     __A				(  UpperCAmelCase       )  ->      Any:




						'''simple docstring'''
						while True:
												_UpperCamelCase      :      Optional[int]       =    root.get_left()
												if left_child is None:
																		break
												_UpperCamelCase      :      List[Any]       =    left_child
						return root.get_data()
def     __A				(  UpperCAmelCase  ,UpperCAmelCase       )  ->      Optional[int]:




						'''simple docstring'''
						_UpperCamelCase      :      str       =    root.get_left()
						_UpperCamelCase      :      Optional[Any]       =    root.get_right()
						if root.get_data() == data:
												if left_child is not None and right_child is not None:
																		_UpperCamelCase      :      List[Any]       =    get_left_most(__lowercase       )
																		root.set_data(__lowercase       )
																		root.set_right(del_node(__lowercase  ,__lowercase       )       )
												elif left_child is not None:
																		_UpperCamelCase      :      List[str]       =    left_child
												elif right_child is not None:
																		_UpperCamelCase      :      Union[str, 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()       ):
																		_UpperCamelCase      :      List[str]       =    left_rotation(__lowercase       )
												else:
																		_UpperCamelCase      :      Tuple       =    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()       ):
																		_UpperCamelCase      :      Tuple       =    right_rotation(__lowercase       )
												else:
																		_UpperCamelCase      :      Optional[Any]       =    lr_rotation(__lowercase       )
						_UpperCamelCase      :      int       =    my_max(get_height(root.get_right()       )  ,get_height(root.get_left()       )       ) + 1
						root.set_height(__lowercase       )
						return root




class 		SCREAMING_SNAKE_CASE  :







				'''simple docstring'''





				def __init__(    self       :    Any       )				->None:


										'''simple docstring'''




										_UpperCamelCase      :      Optional[int]       =    None





				def 			snake_case__					(    self       :    str       )				->int:


										'''simple docstring'''




										return get_height(self.root       )





				def 			snake_case__					(    self       :    Dict							,		lowercase__       :    Any       )				->None:


										'''simple docstring'''




										print("insert:" + str(_UpperCAmelCase       )       )
										_UpperCamelCase      :      Optional[int]       =    insert_node(self.root							,		_UpperCAmelCase       )





				def 			snake_case__					(    self       :    Tuple							,		lowercase__       :    Optional[Any]       )				->None:


										'''simple docstring'''




										print("delete:" + str(_UpperCAmelCase       )       )
										if self.root is None:
																print("Tree is empty!"       )
																return
										_UpperCamelCase      :      str       =    del_node(self.root							,		_UpperCAmelCase       )







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


										'''simple docstring'''




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





def     __A				(  )  ->      List[str]:




						'''simple docstring'''
						import doctest

						doctest.testmod()


if __name__ == "__main__":
			_test()
			lowerCAmelCase_						:		Optional[Any]								=  AVLtree()
			lowerCAmelCase_						:		Union[str, Any]								=  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))










from __future__ import annotations

import unittest

from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property

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


if is_tf_available():
 import tensorflow as tf

 from transformers import TFAutoModelForSeqaSeqLM, TFMBartForConditionalGeneration, TFMBartModel


@require_tf
class     _a							:






  """simple docstring"""





  A_						       = MBartConfig
  A_						       = {}
  A_						       = """gelu"""




  def __init__(  self		,		_UpperCAmelCase		,		_UpperCAmelCase=13		,		_UpperCAmelCase=7		,		_UpperCAmelCase=True		,		_UpperCAmelCase=False		,		_UpperCAmelCase=99		,		_UpperCAmelCase=32		,		_UpperCAmelCase=2		,		_UpperCAmelCase=4		,		_UpperCAmelCase=37		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=20		,		_UpperCAmelCase=2		,		_UpperCAmelCase=1		,		_UpperCAmelCase=0		,		)      ->			Union[str, Any]:
     UpperCamelCase_						=  parent
     UpperCamelCase_						=  batch_size
     UpperCamelCase_						=  seq_length
     UpperCamelCase_						=  is_training
     UpperCamelCase_						=  use_labels
     UpperCamelCase_						=  vocab_size
     UpperCamelCase_						=  hidden_size
     UpperCamelCase_						=  num_hidden_layers
     UpperCamelCase_						=  num_attention_heads
     UpperCamelCase_						=  intermediate_size
     UpperCamelCase_						=  hidden_dropout_prob
     UpperCamelCase_						=  attention_probs_dropout_prob
     UpperCamelCase_						=  max_position_embeddings
     UpperCamelCase_						=  eos_token_id
     UpperCamelCase_						=  pad_token_id
     UpperCamelCase_						=  bos_token_id




  def  _UpperCAmelCase  (  self			)      ->			List[Any]:
     UpperCamelCase_						=  ids_tensor([self.batch_size, self.seq_length - 1]		,		self.vocab_size			)
     UpperCamelCase_						=  tf.expand_dims(tf.constant([self.eos_token_id] * self.batch_size			)		,		1			)
     UpperCamelCase_						=  tf.concat([input_ids, eos_tensor]		,		axis=1			)

     UpperCamelCase_						=  ids_tensor([self.batch_size, self.seq_length]		,		self.vocab_size			)

     UpperCamelCase_						=  self.config_cls(
         vocab_size=self.vocab_size		,		d_model=self.hidden_size		,		encoder_layers=self.num_hidden_layers		,		decoder_layers=self.num_hidden_layers		,		encoder_attention_heads=self.num_attention_heads		,		decoder_attention_heads=self.num_attention_heads		,		encoder_ffn_dim=self.intermediate_size		,		decoder_ffn_dim=self.intermediate_size		,		dropout=self.hidden_dropout_prob		,		attention_dropout=self.attention_probs_dropout_prob		,		max_position_embeddings=self.max_position_embeddings		,		eos_token_ids=[2]		,		bos_token_id=self.bos_token_id		,		pad_token_id=self.pad_token_id		,		decoder_start_token_id=self.pad_token_id		,		**self.config_updates		,		)
     UpperCamelCase_						=  prepare_mbart_inputs_dict(_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase			)
     return config, inputs_dict




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase		,		_UpperCAmelCase			)      ->			List[str]:
     UpperCamelCase_						=  TFMBartModel(config=_UpperCAmelCase			).get_decoder()
     UpperCamelCase_						=  inputs_dict['input_ids']

     UpperCamelCase_						=  input_ids[:1, :]
     UpperCamelCase_						=  inputs_dict['attention_mask'][:1, :]
     UpperCamelCase_						=  inputs_dict['head_mask']
     UpperCamelCase_						=  1

     # first forward pass
     UpperCamelCase_						=  model(_UpperCAmelCase		,		attention_mask=_UpperCAmelCase		,		head_mask=_UpperCAmelCase		,		use_cache=_UpperCAmelCase			)

     UpperCamelCase_		,   UpperCamelCase_						=  outputs.to_tuple()
     UpperCamelCase_						=  past_key_values[1]






def      _snake_case     (__lowercase     ,   __lowercase     ,   __lowercase     ,   __lowercase=None     ,   __lowercase=None     ,   __lowercase=None     ,   __lowercase=None     ,   __lowercase=None     ,   ):
   if attention_mask is None:
      UpperCamelCase_						=  tf.cast(tf.math.not_equal(__lowercase     ,   config.pad_token_id)     ,   tf.inta)
   if decoder_attention_mask is None:
      UpperCamelCase_						=  tf.concat(
          [
              tf.ones(decoder_input_ids[:, :1].shape     ,   dtype=tf.inta),
              tf.cast(tf.math.not_equal(decoder_input_ids[:, 1:]     ,   config.pad_token_id)     ,   tf.inta),
          ]     ,   axis=-1     ,   )
   if head_mask is None:
      UpperCamelCase_						=  tf.ones((config.encoder_layers, config.encoder_attention_heads))
   if decoder_head_mask is None:
      UpperCamelCase_						=  tf.ones((config.decoder_layers, config.decoder_attention_heads))
   if cross_attn_head_mask is None:
      UpperCamelCase_						=  tf.ones((config.decoder_layers, config.decoder_attention_heads))
   return {
       "input_ids": input_ids,
       "decoder_input_ids": decoder_input_ids,
       "attention_mask": attention_mask,
       "decoder_attention_mask": decoder_attention_mask,
       "head_mask": head_mask,
       "decoder_head_mask": decoder_head_mask,
       "cross_attn_head_mask": cross_attn_head_mask,
   }


@require_tf
class     _a							(	UpperCAmelCase__    ,							UpperCAmelCase__    ,							unittest.TestCase     ):






  """simple docstring"""





  A_						       = (TFMBartForConditionalGeneration, TFMBartModel) if is_tf_available() else ()
  A_						       = (TFMBartForConditionalGeneration,) if is_tf_available() else ()
  A_						       = (
      {
          """conversational""": TFMBartForConditionalGeneration,
          """feature-extraction""": TFMBartModel,
          """summarization""": TFMBartForConditionalGeneration,
          """text2text-generation""": TFMBartForConditionalGeneration,
          """translation""": TFMBartForConditionalGeneration,
      }
      if is_tf_available()
      else {}
  )
  A_						       = True
  A_						       = False
  A_						       = False




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase			)      ->			Tuple:
     if pipeline_test_casse_name != "FeatureExtractionPipelineTests":
        # Exception encountered when calling layer '...'
        return True

     return False




  def  _UpperCAmelCase  (  self			)      ->			Optional[int]:
     UpperCamelCase_						=  TFMBartModelTester(self			)
     UpperCamelCase_						=  ConfigTester(self		,		config_class=_UpperCAmelCase			)




  def  _UpperCAmelCase  (  self			)      ->			Optional[int]:
     self.config_tester.run_common_tests()




  def  _UpperCAmelCase  (  self			)      ->			List[Any]:
     UpperCamelCase_						=  self.model_tester.prepare_config_and_inputs_for_common()
     self.model_tester.check_decoder_model_past_large_inputs(*_UpperCAmelCase			)




@require_sentencepiece
@require_tokenizers
@require_tf
class     _a							(	unittest.TestCase     ):






  """simple docstring"""





  A_						       = [
      """ UN Chief Says There Is No Military Solution in Syria""",
  ]
  A_						       = [
      """Şeful ONU declară că nu există o soluţie militară în Siria""",
  ]
  A_						       = """facebook/mbart-large-en-ro"""




  @cached_property
  def  _UpperCAmelCase  (  self			)      ->			Any:
     return AutoTokenizer.from_pretrained(self.model_name			)




  @cached_property
  def  _UpperCAmelCase  (  self			)      ->			List[str]:
     UpperCamelCase_						=  TFAutoModelForSeqaSeqLM.from_pretrained(self.model_name			)
     return model




  def  _UpperCAmelCase  (  self		,		**_UpperCAmelCase			)      ->			int:
     UpperCamelCase_						=  self.translate_src_text(**_UpperCAmelCase			)
     self.assertListEqual(self.expected_text		,		_UpperCAmelCase			)




  def  _UpperCAmelCase  (  self		,		**_UpperCAmelCase			)      ->			List[str]:
     UpperCamelCase_						=  self.tokenizer(self.src_text		,		**_UpperCAmelCase		,		return_tensors='tf'			)
     UpperCamelCase_						=  self.model.generate(
         model_inputs.input_ids		,		attention_mask=model_inputs.attention_mask		,		num_beams=2			)
     UpperCamelCase_						=  self.tokenizer.batch_decode(_UpperCAmelCase		,		skip_special_tokens=_UpperCAmelCase			)
     return generated_words




  @slow
  def  _UpperCAmelCase  (  self			)      ->			List[Any]:
     self._assert_generated_batch_equal_expected()





