



from typing import Any



class 				__snake_case						:




							def __init__(       self     :       Optional[int]				,				A_     :       Any):
									lowerCAmelCase_			:     int									= data
									lowerCAmelCase_			:     Any									= None







							def __repr__(       self     :       Any):
									return F"""Node({self.data})"""





class 				__snake_case						:




							def __init__(       self     :       List[str]):
									lowerCAmelCase_			:     Optional[int]									= None




							def __iter__(       self     :       Optional[int]):
									lowerCAmelCase_			:     List[Any]									= self.head
									while node:
											yield node.data
											lowerCAmelCase_			:     int									= node.next




							def __len__(       self     :       List[Any]):
									return sum(1 for _ in self)




							def __repr__(       self     :       List[str]):
									return "->".join([str(A_) for item in self])




							def __getitem__(       self     :       Optional[int]				,				A_     :       int):
									if not 0 <= index < len(self):
											raise ValueError('''list index out of range.''')
									for i, node in enumerate(self):
											if i == index:
													return node
									return None




							def __setitem__(       self     :       str				,				A_     :       int				,				A_     :       Any):
									if not 0 <= index < len(self):
											raise ValueError('''list index out of range.''')
									lowerCAmelCase_			:     Optional[Any]									= self.head
									for _ in range(A_):
											lowerCAmelCase_			:     Tuple									= current.next
									lowerCAmelCase_			:     List[str]									= data




							def    UpperCAmelCase__			(       self     :       List[Any]				,				A_     :       Any):
									self.insert_nth(len(self)				,				A_)




							def    UpperCAmelCase__			(       self     :       Optional[int]				,				A_     :       Any):
									self.insert_nth(0				,				A_)




							def    UpperCAmelCase__			(       self     :       Tuple				,				A_     :       int				,				A_     :       Any):
									if not 0 <= index <= len(self):
											raise IndexError('''list index out of range''')
									lowerCAmelCase_			:     Any									= Node(A_)
									if self.head is None:
											lowerCAmelCase_			:     Any									= new_node
									elif index == 0:
											lowerCAmelCase_			:     List[Any]									= self.head  # link new_node to head
											lowerCAmelCase_			:     Union[str, Any]									= new_node
									else:
											lowerCAmelCase_			:     Optional[Any]									= self.head
											for _ in range(index - 1):
													lowerCAmelCase_			:     Union[str, Any]									= temp.next
											lowerCAmelCase_			:     str									= temp.next
											lowerCAmelCase_			:     List[str]									= new_node




							def    UpperCAmelCase__			(       self     :       List[Any]):  # print every node data
									print(self)




							def    UpperCAmelCase__			(       self     :       str):
									return self.delete_nth(0)




							def    UpperCAmelCase__			(       self     :       Any):  # delete from tail
									return self.delete_nth(len(self) - 1)




							def    UpperCAmelCase__			(       self     :       Union[str, Any]				,				A_     :       int = 0):
									if not 0 <= index <= len(self) - 1:  # test if index is valid
											raise IndexError('''List index out of range.''')
									lowerCAmelCase_			:     Optional[Any]									= self.head  # default first node
									if index == 0:
											lowerCAmelCase_			:     Any									= self.head.next
									else:
											lowerCAmelCase_			:     int									= self.head
											for _ in range(index - 1):
													lowerCAmelCase_			:     Dict									= temp.next
											lowerCAmelCase_			:     Any									= temp.next
											lowerCAmelCase_			:     str									= temp.next.next
									return delete_node.data




							def    UpperCAmelCase__			(       self     :       str):
									return self.head is None







							def    UpperCAmelCase__			(       self     :       int):
									lowerCAmelCase_			:     Tuple									= None
									lowerCAmelCase_			:     List[Any]									= self.head

									while current:
											# Store the current node's next node.
											lowerCAmelCase_			:     Optional[int]									= current.next
											# Make the current node's next point backwards
											lowerCAmelCase_			:     Tuple									= prev
											# Make the previous node be the current node
											lowerCAmelCase_			:     int									= current
											# Make the current node the next node (to progress iteration)
											lowerCAmelCase_			:     List[Any]									= next_node
									# Return prev in order to put the head at the end
									lowerCAmelCase_			:     Tuple									= prev





def 			UpperCamelCase(  ):
		lowerCAmelCase_			:     int									= LinkedList()
		assert linked_list.is_empty() is True
		assert str(__UpperCamelCase ) == ""

		try:
				linked_list.delete_head()
				raise AssertionError  # This should not happen.
		except IndexError:
				assert True  # This should happen.

		try:
				linked_list.delete_tail()
				raise AssertionError  # This should not happen.
		except IndexError:
				assert True  # This should happen.

		for i in range(10 ):
				assert len(__UpperCamelCase ) == i
				linked_list.insert_nth(__UpperCamelCase     ,i + 1 )
		assert str(__UpperCamelCase ) == "->".join(str(__UpperCamelCase ) for i in range(1     ,11 ) )

		linked_list.insert_head(0 )
		linked_list.insert_tail(11 )
		assert str(__UpperCamelCase ) == "->".join(str(__UpperCamelCase ) for i in range(0     ,12 ) )

		assert linked_list.delete_head() == 0
		assert linked_list.delete_nth(9 ) == 10
		assert linked_list.delete_tail() == 11
		assert len(__UpperCamelCase ) == 9
		assert str(__UpperCamelCase ) == "->".join(str(__UpperCamelCase ) for i in range(1     ,10 ) )

		assert all(linked_list[i] == i + 1 for i in range(0     ,9 ) ) is True

		for i in range(0     ,9 ):
				lowerCAmelCase_			:     int									= -i
		assert all(linked_list[i] == -i for i in range(0     ,9 ) ) is True

		linked_list.reverse()
		assert str(__UpperCamelCase ) == "->".join(str(__UpperCamelCase ) for i in range(-8     ,1 ) )


def 			UpperCamelCase(  ):
		lowerCAmelCase_			:     Dict									= [
		    -9,
		    100,
		    Node(77345112 ),
		    '''dlrow olleH''',
		    7,
		    5555,
		    0,
		    -1_9_2.5_5_5_5_5,
		    '''Hello, world!''',
		    7_7.9,
		    Node(10 ),
		    None,
		    None,
		    1_2.2_0,
		]
		lowerCAmelCase_			:     Any									= LinkedList()

		for i in test_input:
				linked_list.insert_tail(__UpperCamelCase )

		# Check if it's empty or not
		assert linked_list.is_empty() is False
		assert (
		    str(__UpperCamelCase ) == "-9->100->Node(77345112)->dlrow olleH->7->5555->0->"
		    "-192.55555->Hello, world!->77.9->Node(10)->None->None->12.2"
		)

		# Delete the head
		lowerCAmelCase_			:     int									= linked_list.delete_head()
		assert result == -9
		assert (
		    str(__UpperCamelCase ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
		    "Hello, world!->77.9->Node(10)->None->None->12.2"
		)

		# Delete the tail
		lowerCAmelCase_			:     Optional[int]									= linked_list.delete_tail()
		assert result == 1_2.2
		assert (
		    str(__UpperCamelCase ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
		    "Hello, world!->77.9->Node(10)->None->None"
		)

		# Delete a node in specific location in linked list
		lowerCAmelCase_			:     Dict									= linked_list.delete_nth(10 )
		assert result is None
		assert (
		    str(__UpperCamelCase ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
		    "Hello, world!->77.9->Node(10)->None"
		)

		# Add a Node instance to its head
		linked_list.insert_head(Node('''Hello again, world!''' ) )
		assert (
		    str(__UpperCamelCase )
		    == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
		    "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None"
		)

		# Add None to its tail
		linked_list.insert_tail(__UpperCamelCase )
		assert (
		    str(__UpperCamelCase )
		    == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
		    "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None->None"
		)

		# Reverse the linked list
		linked_list.reverse()
		assert (
		    str(__UpperCamelCase )
		    == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
		    "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
		)


def 			UpperCamelCase(  ):
		from doctest import testmod

		testmod()

		lowerCAmelCase_			:     Any									= LinkedList()
		linked_list.insert_head(input('''Inserting 1st at head ''' ).strip() )
		linked_list.insert_head(input('''Inserting 2nd at head ''' ).strip() )
		print('''\nPrint list:''' )
		linked_list.print_list()
		linked_list.insert_tail(input('''\nInserting 1st at tail ''' ).strip() )
		linked_list.insert_tail(input('''Inserting 2nd at tail ''' ).strip() )
		print('''\nPrint list:''' )
		linked_list.print_list()
		print('''\nDelete head''' )
		linked_list.delete_head()
		print('''Delete tail''' )
		linked_list.delete_tail()
		print('''\nPrint list:''' )
		linked_list.print_list()
		print('''\nReverse linked list''' )
		linked_list.reverse()
		print('''\nPrint list:''' )
		linked_list.print_list()
		print('''\nString representation of linked list:''' )
		print(__UpperCamelCase )
		print('''\nReading/changing Node data using indexing:''' )
		print(f"""Element at Position 1: {linked_list[1]}""" )
		lowerCAmelCase_			:     Optional[Any]									= input('''Enter New Value: ''' ).strip()
		print('''New list:''' )
		print(__UpperCamelCase )
		print(f"""length of linked_list is : {len(__UpperCamelCase )}""" )


if __name__ == "__main__":
						main()









import unittest

from transformers import (
    MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
    TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
    TextClassificationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow

from .test_pipelines_common import ANY


# These 2 model types require different inputs than those of the usual text models.
UpperCAmelCase_      : Dict  					=       {'LayoutLMv2Config', 'LayoutLMv3Config'}
@is_pipeline_test
class  SCREAMING_SNAKE_CASE__  (				unittest.TestCase			):
      snake_case__				:     List[str]        =						MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING
      snake_case__				:     Optional[Any]        =						TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING

      if model_mapping is not None:
            snake_case__				:     str        =						{config: model for config, model in model_mapping.items() if config.__name__ not in _TO_SKIP}
      if tf_model_mapping is not None:
            snake_case__				:     List[Any]        =						{
                config: model for config, model in tf_model_mapping.items() if config.__name__ not in _TO_SKIP
            }
      @require_torch
      def        SCREAMING_SNAKE_CASE							(       self				:       Tuple     )		->			Tuple:
             a_					:		List[Any]							=  pipeline(
                 task='text-classification'     ,							model='hf-internal-testing/tiny-random-distilbert'     ,							framework='pt'     )

             a_					:		int							=  text_classifier('This is great !'     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'LABEL_0', 'score': 0.504}]     )

             a_					:		Tuple							=  text_classifier('This is great !'     ,							top_k=2     )
             self.assertEqual(
                 nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'LABEL_0', 'score': 0.504}, {'label': 'LABEL_1', 'score': 0.496}]     )

             a_					:		List[str]							=  text_classifier(['This is great !', 'This is bad']     ,							top_k=2     )
             self.assertEqual(
                 nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[
                     [{'label': 'LABEL_0', 'score': 0.504}, {'label': 'LABEL_1', 'score': 0.496}],
                     [{'label': 'LABEL_0', 'score': 0.504}, {'label': 'LABEL_1', 'score': 0.496}],
                 ]     ,							)

             a_					:		Tuple							=  text_classifier('This is great !'     ,							top_k=1     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'LABEL_0', 'score': 0.504}]     )

             # Legacy behavior
             a_					:		Union[str, Any]							=  text_classifier('This is great !'     ,							return_all_scores=SCREAMING_SNAKE_CASE__     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'LABEL_0', 'score': 0.504}]     )

             a_					:		List[str]							=  text_classifier('This is great !'     ,							return_all_scores=SCREAMING_SNAKE_CASE__     )
             self.assertEqual(
                 nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[[{'label': 'LABEL_0', 'score': 0.504}, {'label': 'LABEL_1', 'score': 0.496}]]     )

             a_					:		int							=  text_classifier(['This is great !', 'Something else']     ,							return_all_scores=SCREAMING_SNAKE_CASE__     )
             self.assertEqual(
                 nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[
                     [{'label': 'LABEL_0', 'score': 0.504}, {'label': 'LABEL_1', 'score': 0.496}],
                     [{'label': 'LABEL_0', 'score': 0.504}, {'label': 'LABEL_1', 'score': 0.496}],
                 ]     ,							)

             a_					:		str							=  text_classifier(['This is great !', 'Something else']     ,							return_all_scores=SCREAMING_SNAKE_CASE__     )
             self.assertEqual(
                 nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[
                     {'label': 'LABEL_0', 'score': 0.504},
                     {'label': 'LABEL_0', 'score': 0.504},
                 ]     ,							)
      @require_torch
      def        SCREAMING_SNAKE_CASE							(       self				:       int     )		->			Dict:
             import torch

             a_					:		List[Any]							=  pipeline(
                 task='text-classification'     ,							model='hf-internal-testing/tiny-random-distilbert'     ,							framework='pt'     ,							device=torch.device('cpu'     )     ,							)

             a_					:		Any							=  text_classifier('This is great !'     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'LABEL_0', 'score': 0.504}]     )
      @require_tf
      def        SCREAMING_SNAKE_CASE							(       self				:       str     )		->			Optional[Any]:
             a_					:		List[str]							=  pipeline(
                 task='text-classification'     ,							model='hf-internal-testing/tiny-random-distilbert'     ,							framework='tf'     )

             a_					:		Optional[int]							=  text_classifier('This is great !'     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'LABEL_0', 'score': 0.504}]     )
      @slow
      @require_torch
      def        SCREAMING_SNAKE_CASE							(       self				:       Dict     )		->			Optional[int]:
             a_					:		List[str]							=  pipeline('text-classification'     )

             a_					:		Dict							=  text_classifier('This is great !'     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'POSITIVE', 'score': 1.0}]     )
             a_					:		Union[str, Any]							=  text_classifier('This is bad !'     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'NEGATIVE', 'score': 1.0}]     )
             a_					:		Tuple							=  text_classifier('Birds are a type of animal'     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'POSITIVE', 'score': 0.988}]     )
      @slow
      @require_tf
      def        SCREAMING_SNAKE_CASE							(       self				:       List[str]     )		->			List[Any]:
             a_					:		Dict							=  pipeline('text-classification'     ,							framework='tf'     )

             a_					:		Optional[Any]							=  text_classifier('This is great !'     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'POSITIVE', 'score': 1.0}]     )
             a_					:		int							=  text_classifier('This is bad !'     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'NEGATIVE', 'score': 1.0}]     )
             a_					:		Optional[int]							=  text_classifier('Birds are a type of animal'     )
             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': 'POSITIVE', 'score': 0.988}]     )
      def        SCREAMING_SNAKE_CASE							(       self				:       Union[str, Any]     ,							SCREAMING_SNAKE_CASE__				:       Any     ,							SCREAMING_SNAKE_CASE__				:       int     ,							SCREAMING_SNAKE_CASE__				:       Optional[Any]     )		->			Any:
             a_					:		Optional[Any]							=  TextClassificationPipeline(model=SCREAMING_SNAKE_CASE__     ,							tokenizer=SCREAMING_SNAKE_CASE__     )
             return text_classifier, ["HuggingFace is in", "This is another test"]

      def        SCREAMING_SNAKE_CASE							(       self				:       Union[str, Any]     ,							SCREAMING_SNAKE_CASE__				:       Any     ,							SCREAMING_SNAKE_CASE__				:       Optional[int]     )		->			Union[str, Any]:
             a_					:		List[str]							=  text_classifier.model
             # Small inputs because BartTokenizer tiny has maximum position embeddings = 22
             a_					:		Union[str, Any]							=  'HuggingFace is in'
             a_					:		int							=  text_classifier(SCREAMING_SNAKE_CASE__     )

             self.assertEqual(nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': ANY(SCREAMING_SNAKE_CASE__     ), 'score': ANY(SCREAMING_SNAKE_CASE__     )}]     )
             self.assertTrue(outputs[0]['label'] in model.config.idalabel.values()     )

             a_					:		Union[str, Any]							=  ['HuggingFace is in ', 'Paris is in France']
             a_					:		int							=  text_classifier(SCREAMING_SNAKE_CASE__     )
             self.assertEqual(
                 nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': ANY(SCREAMING_SNAKE_CASE__     ), 'score': ANY(SCREAMING_SNAKE_CASE__     )}, {'label': ANY(SCREAMING_SNAKE_CASE__     ), 'score': ANY(SCREAMING_SNAKE_CASE__     )}]     ,							)
             self.assertTrue(outputs[0]['label'] in model.config.idalabel.values()     )
             self.assertTrue(outputs[1]['label'] in model.config.idalabel.values()     )

             # Forcing to get all results with `top_k=None`
             # This is NOT the legacy format
             a_					:		List[Any]							=  text_classifier(SCREAMING_SNAKE_CASE__     ,							top_k=SCREAMING_SNAKE_CASE__     )
             a_					:		Dict							=  len(model.config.idalabel.values()     )
             self.assertEqual(
                 nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[[{'label': ANY(SCREAMING_SNAKE_CASE__     ), 'score': ANY(SCREAMING_SNAKE_CASE__     )}] * N, [{'label': ANY(SCREAMING_SNAKE_CASE__     ), 'score': ANY(SCREAMING_SNAKE_CASE__     )}] * N]     ,							)

             a_					:		int							=  {'text': 'HuggingFace is in ', 'text_pair': 'Paris is in France'}
             a_					:		Optional[int]							=  text_classifier(SCREAMING_SNAKE_CASE__     )
             self.assertEqual(
                 nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							{'label': ANY(SCREAMING_SNAKE_CASE__     ), 'score': ANY(SCREAMING_SNAKE_CASE__     )}     ,							)
             self.assertTrue(outputs['label'] in model.config.idalabel.values()     )

             # This might be used a text pair, but tokenizer + pipe interaction
             # makes it hard to understand that it's not using the pair properly
             # https://github.com/huggingface/transformers/issues/17305
             # We disabled this usage instead as it was outputting wrong outputs.
             a_					:		Any							=  [['HuggingFace is in ', 'Paris is in France']]
             with self.assertRaises(SCREAMING_SNAKE_CASE__     ):
                    text_classifier(SCREAMING_SNAKE_CASE__     )

             # This used to be valid for doing text pairs
             # We're keeping it working because of backward compatibility
             a_					:		Tuple							=  text_classifier([[['HuggingFace is in ', 'Paris is in France']]]     )
             self.assertEqual(
                 nested_simplify(SCREAMING_SNAKE_CASE__     )     ,							[{'label': ANY(SCREAMING_SNAKE_CASE__     ), 'score': ANY(SCREAMING_SNAKE_CASE__     )}]     ,							)
             self.assertTrue(outputs[0]['label'] in model.config.idalabel.values()     )


