
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_       (      __lowerCamelCase       ):




	'''simple docstring'''


	_UpperCamelCase					:					Dict										=	DPRContextEncoderTokenizer
	_UpperCamelCase					:					Optional[int]										=	DPRContextEncoderTokenizerFast
	_UpperCamelCase					:					Dict										=	True







@require_tokenizers
class 	A_       (      __lowerCamelCase       ):




	'''simple docstring'''


	_UpperCamelCase					:					List[str]										=	DPRQuestionEncoderTokenizer
	_UpperCamelCase					:					Union[str, Any]										=	DPRQuestionEncoderTokenizerFast
	_UpperCamelCase					:					str										=	True







@require_tokenizers
class 	A_       (      __lowerCamelCase       ):




	'''simple docstring'''


	_UpperCamelCase					:					Tuple										=	DPRReaderTokenizer
	_UpperCamelCase					:					List[str]										=	DPRReaderTokenizerFast
	_UpperCamelCase					:					Optional[Any]										=	True





	@slow
	def      SCREAMING_SNAKE_CASE__						(	self	):
		lowercase					  =   self.tokenizer_class.from_pretrained('bert-base-uncased'	)

		lowercase					  =   tokenizer.encode('question sequence'		,   add_special_tokens=snake_case	)
		lowercase					  =   tokenizer.encode('title sequence'		,   add_special_tokens=snake_case	)
		lowercase					  =   tokenizer.encode('text sequence ' * 4		,   add_special_tokens=snake_case	)
		lowercase					  =   [[101] + text_a + [102] + text_a + [102] + text_a]
		lowercase					  =   BatchEncoding({'input_ids': input_ids}	)

		lowercase					  =   [[0] * len(input_ids[0]	)]
		lowercase					  =   [[0] * len(input_ids[0]	)]
		lowercase					  =   [0]
		lowercase					  =   DPRReaderOutput(snake_case		,   snake_case		,   snake_case	)

		lowercase  , lowercase					  =   8, 9
		lowercase					  =   10
		lowercase					  =   10
		lowercase					  =   tokenizer.decode_best_spans(snake_case		,   snake_case	)
		self.assertEqual(predicted_spans[0].start_index		,   snake_case	)
		self.assertEqual(predicted_spans[0].end_index		,   snake_case	)
		self.assertEqual(predicted_spans[0].doc_id		,   0	)





	@slow
	def      SCREAMING_SNAKE_CASE__						(	self	):
		lowercase					  =   self.tokenizer_class.from_pretrained('bert-base-uncased'	)

		lowercase					  =   tokenizer.encode('question sequence'		,   add_special_tokens=snake_case	)
		lowercase					  =   tokenizer.encode('title sequence'		,   add_special_tokens=snake_case	)
		lowercase					  =   tokenizer.encode('text sequence'		,   add_special_tokens=snake_case	)
		lowercase					  =   [101] + text_a + [102] + text_a + [102] + text_a
		lowercase					  =   tokenizer(questions=['question sequence']		,   titles=['title sequence']		,   texts=['text sequence']	)
		self.assertIn('input_ids'		,   snake_case	)
		self.assertIn('attention_mask'		,   snake_case	)
		self.assertListEqual(encoded_input['input_ids'][0]		,   snake_case	)



from __future__ import annotations

from queue import Queue







class 	A_       :




	'''simple docstring'''


	def __init__(	self	):
		lowercase					  =   {}





	def      SCREAMING_SNAKE_CASE__						(	self	):
		for i in self.vertices:
			print(snake_case		,   ' : '		,   ' -> '.join([str(snake_case	) for j in self.vertices[i]]	)	)





	def      SCREAMING_SNAKE_CASE__						(	self		,   snake_case		,   snake_case	):
		if from_vertex in self.vertices:
			self.vertices[from_vertex].append(snake_case	)
		else:
			lowercase					  =   [to_vertex]





	def      SCREAMING_SNAKE_CASE__						(	self		,   snake_case	):
		lowercase					  =   set()

		# create a first in first out queue to store all the vertices for BFS
		lowercase					  =   Queue()

		# mark the source node as visited and enqueue it
		visited.add(snake_case	)
		queue.put(snake_case	)

		while not queue.empty():
			lowercase					  =   queue.get()

			# loop through all adjacent vertex and enqueue it if not yet visited
			for adjacent_vertex in self.vertices[vertex]:
				if adjacent_vertex not in visited:
					queue.put(snake_case	)
					visited.add(snake_case	)
		return visited


if __name__ == "__main__":
	from doctest import testmod

	testmod(verbose=True)

	UpperCAmelCase     				=			Graph()
	g.add_edge(0, 1)
	g.add_edge(0, 2)
	g.add_edge(1, 2)
	g.add_edge(2, 0)
	g.add_edge(2, 3)
	g.add_edge(3, 3)

	g.print_graph()
	# 0  :  1 -> 2
	# 1  :  2
	# 2  :  0 -> 3
	# 3  :  3

	assert sorted(g.bfs(2)) == [0, 1, 2, 3]

