



'''simple docstring'''
from __future__ import annotations

from typing import Generic, TypeVar

_UpperCamelCase									=      TypeVar('''T''')



class _A	(     Generic[T]     ):





		def __init__(  self			,							__UpperCAmelCase					)							->  int:

					'''simple docstring'''
					__UpperCAmelCase :   Tuple    					=  data  # Assign data
					__UpperCAmelCase :   Node[T] | None    					=  None  # Initialize next as null
					__UpperCAmelCase :   Node[T] | None    					=  None  # Initialize prev as null



class _A	(     Generic[T]     ):





		def __init__(  self					)							->  None:

					'''simple docstring'''
					__UpperCAmelCase :   Node[T] | None    					=  None





		def 				__A							(  self			,							__UpperCAmelCase					)							->  None:

					'''simple docstring'''
					if self.head is None:
								__UpperCAmelCase :   Tuple    					=  Node(__UpperCAmelCase					)
					else:
								__UpperCAmelCase :   Dict    					=  Node(__UpperCAmelCase					)
								__UpperCAmelCase :   str    					=  new_node
								__UpperCAmelCase :   Optional[Any]    					=  self.head
								__UpperCAmelCase :   Optional[int]    					=  None
								__UpperCAmelCase :   Optional[Any]    					=  new_node





		def 				__A							(  self					)							->  T | None:

					'''simple docstring'''
					if self.head is None:
								return None
					else:
								assert self.head is not None
								__UpperCAmelCase :   Dict    					=  self.head.data
								__UpperCAmelCase :   Union[str, Any]    					=  self.head.next
								if self.head is not None:
											__UpperCAmelCase :   Union[str, Any]    					=  None
								return temp





		def 				__A							(  self					)							->  T | None:

					'''simple docstring'''
					return self.head.data if self.head is not None else None





		def __len__(  self					)							->  int:

					'''simple docstring'''
					__UpperCAmelCase :   Union[str, Any]    					=  self.head
					__UpperCAmelCase :   List[Any]    					=  0
					while temp is not None:
								count += 1
								__UpperCAmelCase :   Optional[int]    					=  temp.next
					return count





		def 				__A							(  self					)							->  bool:

					'''simple docstring'''
					return self.head is None





		def 				__A							(  self					)							->  None:

					'''simple docstring'''
					print("""stack elements are:"""					)
					__UpperCAmelCase :   str    					=  self.head
					while temp is not None:
								print(temp.data			,							end="""->"""					)
								__UpperCAmelCase :   List[Any]    					=  temp.next


# Code execution starts here
if __name__ == "__main__":
					# Start with the empty stack
					_UpperCamelCase									=      Stack()

					# Insert 4 at the beginning. So stack becomes 4->None
					print('''Stack operations using Doubly LinkedList''')
					stack.push(4)

					# Insert 5 at the beginning. So stack becomes 4->5->None
					stack.push(5)

					# Insert 6 at the beginning. So stack becomes 4->5->6->None
					stack.push(6)

					# Insert 7 at the beginning. So stack becomes 4->5->6->7->None
					stack.push(7)

					# Print the stack
					stack.print_stack()

					# Print the top element
					print('''\nTop element is ''', stack.top())

					# Print the stack size
					print('''Size of the stack is ''', len(stack))

					# pop the top element
					stack.pop()

					# pop the top element
					stack.pop()

					# two elements have now been popped off
					stack.print_stack()

					# Print True if the stack is empty else False
					print('''\nstack is empty:''', stack.is_empty())









'''simple docstring'''
from transformers import (
    DPRContextEncoderTokenizer,
    DPRContextEncoderTokenizerFast,
    DPRQuestionEncoderTokenizer,
    DPRQuestionEncoderTokenizerFast,
    DPRReaderOutput,
    DPRReaderTokenizer,
    DPRReaderTokenizerFast,
)
from transformers.testing_utils import require_tokenizers, slow
from transformers.tokenization_utils_base import BatchEncoding

from ..bert.test_tokenization_bert import BertTokenizationTest



@require_tokenizers
class _A	(     __SCREAMING_SNAKE_CASE     ):
		_SCREAMING_SNAKE_CASE       :     List[str]       =      DPRContextEncoderTokenizer
		_SCREAMING_SNAKE_CASE       :     Optional[int]       =      DPRContextEncoderTokenizerFast
		_SCREAMING_SNAKE_CASE       :     Optional[Any]       =      True



@require_tokenizers
class _A	(     __SCREAMING_SNAKE_CASE     ):
		_SCREAMING_SNAKE_CASE       :     str       =      DPRQuestionEncoderTokenizer
		_SCREAMING_SNAKE_CASE       :     List[str]       =      DPRQuestionEncoderTokenizerFast
		_SCREAMING_SNAKE_CASE       :     Union[str, Any]       =      True



@require_tokenizers
class _A	(     __SCREAMING_SNAKE_CASE     ):
		_SCREAMING_SNAKE_CASE       :     List[str]       =      DPRReaderTokenizer
		_SCREAMING_SNAKE_CASE       :     Optional[Any]       =      DPRReaderTokenizerFast
		_SCREAMING_SNAKE_CASE       :     Dict       =      True





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

					'''simple docstring'''
					__UpperCAmelCase :   Dict    					=  self.tokenizer_class.from_pretrained("""bert-base-uncased"""					)

					__UpperCAmelCase :   int    					=  tokenizer.encode("""question sequence"""			,							add_special_tokens=__UpperCAmelCase					)
					__UpperCAmelCase :   Optional[Any]    					=  tokenizer.encode("""title sequence"""			,							add_special_tokens=__UpperCAmelCase					)
					__UpperCAmelCase :   Any    					=  tokenizer.encode("""text sequence """ * 4			,							add_special_tokens=__UpperCAmelCase					)
					__UpperCAmelCase :   Tuple    					=  [[101] + text_a + [102] + text_a + [102] + text_a]
					__UpperCAmelCase :   Optional[int]    					=  BatchEncoding({"""input_ids""": input_ids}					)

					__UpperCAmelCase :   str    					=  [[0] * len(input_ids[0]					)]
					__UpperCAmelCase :   str    					=  [[0] * len(input_ids[0]					)]
					__UpperCAmelCase :   Optional[int]    					=  [0]
					__UpperCAmelCase :   List[str]    					=  DPRReaderOutput(__UpperCAmelCase			,							__UpperCAmelCase			,							__UpperCAmelCase					)

					__UpperCAmelCase					,	__UpperCAmelCase :   Any    					=  8, 9
					__UpperCAmelCase :   Optional[int]    					=  10
					__UpperCAmelCase :   int    					=  10
					__UpperCAmelCase :   str    					=  tokenizer.decode_best_spans(__UpperCAmelCase			,							__UpperCAmelCase					)
					self.assertEqual(predicted_spans[0].start_index			,							__UpperCAmelCase					)
					self.assertEqual(predicted_spans[0].end_index			,							__UpperCAmelCase					)
					self.assertEqual(predicted_spans[0].doc_id			,							0					)





		@slow
		def 				__A							(  self					)							->  int:

					'''simple docstring'''
					__UpperCAmelCase :   Any    					=  self.tokenizer_class.from_pretrained("""bert-base-uncased"""					)

					__UpperCAmelCase :   List[Any]    					=  tokenizer.encode("""question sequence"""			,							add_special_tokens=__UpperCAmelCase					)
					__UpperCAmelCase :   List[str]    					=  tokenizer.encode("""title sequence"""			,							add_special_tokens=__UpperCAmelCase					)
					__UpperCAmelCase :   Union[str, Any]    					=  tokenizer.encode("""text sequence"""			,							add_special_tokens=__UpperCAmelCase					)
					__UpperCAmelCase :   Optional[int]    					=  [101] + text_a + [102] + text_a + [102] + text_a
					__UpperCAmelCase :   int    					=  tokenizer(questions=["""question sequence"""]			,							titles=["""title sequence"""]			,							texts=["""text sequence"""]					)
					self.assertIn("""input_ids"""			,							__UpperCAmelCase					)
					self.assertIn("""attention_mask"""			,							__UpperCAmelCase					)
					self.assertListEqual(encoded_input["""input_ids"""][0]			,							__UpperCAmelCase					)




