
class   UpperCAmelCase		:



   def __init__(self		:					Tuple    ,						snake_case__		:					int    ,						snake_case__		:					Union[str, Any]=None    ,						snake_case__		:					List[Any]=None )		->	Tuple:


          '''simple docstring'''


          snake_case       :   List[Any]							=      data
          snake_case       :   Tuple							=      previous
          snake_case       :   Tuple							=      next_node



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


          '''simple docstring'''


          return f"""{self.data}"""



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


          '''simple docstring'''


          return self.data



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


          '''simple docstring'''


          return self.next



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


          '''simple docstring'''


          return self.previous






class   UpperCAmelCase		:



   def __init__(self		:					Optional[Any]    ,						snake_case__		:					Any )		->	int:


          '''simple docstring'''


          snake_case       :   Union[str, Any]							=      head



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


          '''simple docstring'''


          return self



   def 				_SCREAMING_SNAKE_CASE   (self		:					str )		->	Any:


          '''simple docstring'''


          if not self.current:
                 raise StopIteration
          else:
                 snake_case       :   str							=      self.current.get_data()
                 snake_case       :   Optional[Any]							=      self.current.get_next()
                 return value






class   UpperCAmelCase		:



   def __init__(self		:					List[Any] )		->	Dict:


          '''simple docstring'''


          snake_case       :   Tuple							=      None  # First node in list
          snake_case       :   int							=      None  # Last node in list



   def __str__(self		:					Dict )		->	Optional[int]:


          '''simple docstring'''


          snake_case       :   List[str]							=      self.head
          snake_case       :   Dict							=      []
          while current is not None:
                 nodes.append(current.get_data() )
                 snake_case       :   Dict							=      current.get_next()
          return " ".join(str(_snake_case ) for node in nodes )



   def __contains__(self		:					Any    ,						snake_case__		:					int )		->	Any:


          '''simple docstring'''


          snake_case       :   List[str]							=      self.head
          while current:
                 if current.get_data() == value:
                        return True
                 snake_case       :   Tuple							=      current.get_next()
          return False



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


          '''simple docstring'''


          return LinkedListIterator(self.head )



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


          '''simple docstring'''


          if self.head:
                 return self.head.get_data()
          return None



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


          '''simple docstring'''


          if self.tail:
                 return self.tail.get_data()
          return None



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


          '''simple docstring'''


          if self.head is None:
                 snake_case       :   Dict							=      node
                 snake_case       :   Dict							=      node
          else:
                 self.insert_before_node(self.head    ,						_snake_case )



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


          '''simple docstring'''


          if self.head is None:
                 self.set_head(_snake_case )
          else:
                 self.insert_after_node(self.tail    ,						_snake_case )



   def 				_SCREAMING_SNAKE_CASE   (self		:					int    ,						snake_case__		:					int )		->	None:


          '''simple docstring'''


          snake_case       :   Any							=      Node(_snake_case )
          if self.head is None:
                 self.set_head(_snake_case )
          else:
                 self.set_tail(_snake_case )



   def 				_SCREAMING_SNAKE_CASE   (self		:					Union[str, Any]    ,						snake_case__		:					Node    ,						snake_case__		:					Node )		->	None:


          '''simple docstring'''


          snake_case       :   Tuple							=      node
          snake_case       :   Optional[Any]							=      node.previous

          if node.get_previous() is None:
                 snake_case       :   Optional[int]							=      node_to_insert
          else:
                 snake_case       :   List[str]							=      node_to_insert

          snake_case       :   Tuple							=      node_to_insert



   def 				_SCREAMING_SNAKE_CASE   (self		:					int    ,						snake_case__		:					Node    ,						snake_case__		:					Node )		->	None:


          '''simple docstring'''


          snake_case       :   Dict							=      node
          snake_case       :   str							=      node.next

          if node.get_next() is None:
                 snake_case       :   int							=      node_to_insert
          else:
                 snake_case       :   Optional[int]							=      node_to_insert

          snake_case       :   Tuple							=      node_to_insert



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


          '''simple docstring'''


          snake_case       :   Dict							=      1
          snake_case       :   Optional[Any]							=      Node(_snake_case )
          snake_case       :   Any							=      self.head
          while node:
                 if current_position == position:
                        self.insert_before_node(_snake_case    ,						_snake_case )
                        return
                 current_position += 1
                 snake_case       :   Optional[Any]							=      node.next
          self.insert_after_node(self.tail    ,						_snake_case )



   def 				_SCREAMING_SNAKE_CASE   (self		:					int    ,						snake_case__		:					int )		->	Node:


          '''simple docstring'''


          snake_case       :   Any							=      self.head
          while node:
                 if node.get_data() == item:
                        return node
                 snake_case       :   Tuple							=      node.get_next()
          raise Exception("Node not found" )



   def 				_SCREAMING_SNAKE_CASE   (self		:					Dict    ,						snake_case__		:					List[Any] )		->	str:


          '''simple docstring'''


          if (node := self.get_node(_snake_case )) is not None:
                 if node == self.head:
                        snake_case       :   List[Any]							=      self.head.get_next()

                 if node == self.tail:
                        snake_case       :   List[Any]							=      self.tail.get_previous()

                 self.remove_node_pointers(_snake_case )



   @staticmethod
   def 				_SCREAMING_SNAKE_CASE   (snake_case__		:					Node )		->	None:


          '''simple docstring'''


          if node.get_next():
                 snake_case       :   int							=      node.previous

          if node.get_previous():
                 snake_case       :   Optional[int]							=      node.next

          snake_case       :   List[Any]							=      None
          snake_case       :   Tuple							=      None



   def 				_SCREAMING_SNAKE_CASE   (self		:					str )		->	str:


          '''simple docstring'''


          return self.head is None



def 			UpperCamelCase					(    ):
       pass


if __name__ == "__main__":
   import doctest

   doctest.testmod()










"""simple docstring"""







from __future__ import annotations

import unittest

from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow


if is_tf_available():
							from transformers import (
							    AutoConfig,
							    BertConfig,
							    GPTaConfig,
							    TaConfig,
							    TFAutoModel,
							    TFAutoModelForCausalLM,
							    TFAutoModelForMaskedLM,
							    TFAutoModelForPreTraining,
							    TFAutoModelForQuestionAnswering,
							    TFAutoModelForSeqaSeqLM,
							    TFAutoModelForSequenceClassification,
							    TFAutoModelWithLMHead,
							    TFBertForMaskedLM,
							    TFBertForPreTraining,
							    TFBertForQuestionAnswering,
							    TFBertForSequenceClassification,
							    TFBertModel,
							    TFGPTaLMHeadModel,
							    TFRobertaForMaskedLM,
							    TFTaForConditionalGeneration,
							)
							from transformers.models.bert.modeling_tf_bert import TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST
							from transformers.models.gpta.modeling_tf_gpta import TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST
							from transformers.models.ta.modeling_tf_ta import TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST

if is_torch_available():
							from transformers import (
							    AutoModel,
							    AutoModelForCausalLM,
							    AutoModelForMaskedLM,
							    AutoModelForPreTraining,
							    AutoModelForQuestionAnswering,
							    AutoModelForSeqaSeqLM,
							    AutoModelForSequenceClassification,
							    AutoModelWithLMHead,
							    BertForMaskedLM,
							    BertForPreTraining,
							    BertForQuestionAnswering,
							    BertForSequenceClassification,
							    BertModel,
							    GPTaLMHeadModel,
							    RobertaForMaskedLM,
							    TaForConditionalGeneration,
							)
@is_pt_tf_cross_test
class        __A       (	unittest.TestCase    ):







		'''simple docstring'''





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






				"""simple docstring"""



				for model_name in ["bert-base-uncased"]:
						lowercase__   :    Tuple				=			AutoConfig.from_pretrained(_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Dict				=			TFAutoModel.from_pretrained(_snake_case			,from_pt=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    List[str]				=			AutoModel.from_pretrained(_snake_case			,from_tf=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)







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






				"""simple docstring"""



				for model_name in ["bert-base-uncased"]:
						lowercase__   :    Dict				=			AutoConfig.from_pretrained(_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    str				=			TFAutoModelForPreTraining.from_pretrained(_snake_case			,from_pt=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Optional[Any]				=			AutoModelForPreTraining.from_pretrained(_snake_case			,from_tf=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)







		@slow
		def 					UpperCAmelCase    (	self						:  Tuple						)					->		Dict:






				"""simple docstring"""



				for model_name in TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
						lowercase__   :    Any				=			AutoConfig.from_pretrained(_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    List[str]				=			TFAutoModelForCausalLM.from_pretrained(_snake_case			,from_pt=_snake_case						)
						lowercase__		,			lowercase__   :    Optional[Any]				=			TFAutoModelForCausalLM.from_pretrained(
						    _snake_case			,output_loading_info=_snake_case			,from_pt=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Union[str, Any]				=			AutoModelForCausalLM.from_pretrained(_snake_case			,from_tf=_snake_case						)
						lowercase__		,			lowercase__   :    Optional[Any]				=			AutoModelForCausalLM.from_pretrained(
						    _snake_case			,output_loading_info=_snake_case			,from_tf=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)







		@slow
		def 					UpperCAmelCase    (	self						:  Any						)					->		Tuple:






				"""simple docstring"""



				for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
						lowercase__   :    Any				=			AutoConfig.from_pretrained(_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Optional[Any]				=			TFAutoModelWithLMHead.from_pretrained(_snake_case			,from_pt=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Any				=			AutoModelWithLMHead.from_pretrained(_snake_case			,from_tf=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)







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






				"""simple docstring"""



				for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
						lowercase__   :    str				=			AutoConfig.from_pretrained(_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Union[str, Any]				=			TFAutoModelForMaskedLM.from_pretrained(_snake_case			,from_pt=_snake_case						)
						lowercase__		,			lowercase__   :    str				=			TFAutoModelForMaskedLM.from_pretrained(
						    _snake_case			,output_loading_info=_snake_case			,from_pt=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    List[str]				=			AutoModelForMaskedLM.from_pretrained(_snake_case			,from_tf=_snake_case						)
						lowercase__		,			lowercase__   :    Any				=			AutoModelForMaskedLM.from_pretrained(
						    _snake_case			,output_loading_info=_snake_case			,from_tf=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)







		@slow
		def 					UpperCAmelCase    (	self						:  List[Any]						)					->		Dict:






				"""simple docstring"""



				for model_name in TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
						lowercase__   :    Union[str, Any]				=			AutoConfig.from_pretrained(_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    List[str]				=			TFAutoModelForSeqaSeqLM.from_pretrained(_snake_case			,from_pt=_snake_case						)
						lowercase__		,			lowercase__   :    List[str]				=			TFAutoModelForSeqaSeqLM.from_pretrained(
						    _snake_case			,output_loading_info=_snake_case			,from_pt=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Any				=			AutoModelForSeqaSeqLM.from_pretrained(_snake_case			,from_tf=_snake_case						)
						lowercase__		,			lowercase__   :    Optional[int]				=			AutoModelForSeqaSeqLM.from_pretrained(
						    _snake_case			,output_loading_info=_snake_case			,from_tf=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)







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






				"""simple docstring"""



				for model_name in ["bert-base-uncased"]:
						lowercase__   :    Tuple				=			AutoConfig.from_pretrained(_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Any				=			TFAutoModelForSequenceClassification.from_pretrained(_snake_case			,from_pt=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Union[str, Any]				=			AutoModelForSequenceClassification.from_pretrained(_snake_case			,from_tf=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)







		@slow
		def 					UpperCAmelCase    (	self						:  Tuple						)					->		Optional[Any]:






				"""simple docstring"""



				for model_name in ["bert-base-uncased"]:
						lowercase__   :    List[Any]				=			AutoConfig.from_pretrained(_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    str				=			TFAutoModelForQuestionAnswering.from_pretrained(_snake_case			,from_pt=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)

						lowercase__   :    Any				=			AutoModelForQuestionAnswering.from_pretrained(_snake_case			,from_tf=_snake_case						)
						self.assertIsNotNone(_snake_case						)
						self.assertIsInstance(_snake_case			,_snake_case						)







		def 					UpperCAmelCase    (	self						:  Dict						)					->		Any:






				"""simple docstring"""



				lowercase__   :    Optional[Any]				=			TFAutoModelWithLMHead.from_pretrained(_snake_case			,from_pt=_snake_case						)
				self.assertIsInstance(_snake_case			,_snake_case						)
				self.assertEqual(model.num_parameters()			,14_410						)
				self.assertEqual(model.num_parameters(only_trainable=_snake_case						)			,14_410						)

				lowercase__   :    Union[str, Any]				=			AutoModelWithLMHead.from_pretrained(_snake_case			,from_tf=_snake_case						)
				self.assertIsInstance(_snake_case			,_snake_case						)
				self.assertEqual(model.num_parameters()			,14_410						)
				self.assertEqual(model.num_parameters(only_trainable=_snake_case						)			,14_410						)







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






				"""simple docstring"""



				lowercase__   :    List[Any]				=			TFAutoModelWithLMHead.from_pretrained(_snake_case			,from_pt=_snake_case						)
				self.assertIsInstance(_snake_case			,_snake_case						)
				self.assertEqual(model.num_parameters()			,14_410						)
				self.assertEqual(model.num_parameters(only_trainable=_snake_case						)			,14_410						)

				lowercase__   :    int				=			AutoModelWithLMHead.from_pretrained(_snake_case			,from_tf=_snake_case						)
				self.assertIsInstance(_snake_case			,_snake_case						)
				self.assertEqual(model.num_parameters()			,14_410						)
				self.assertEqual(model.num_parameters(only_trainable=_snake_case						)			,14_410						)
