


"""simple docstring"""






from __future__ import annotations

from queue import Queue


class 	A_       :





  """simple docstring"""

  def __init__(						self						)				->					None:
     a   :	dict[int, list[int]]						=    {}
  def 							lowercase_     (						self						)				->					None:
     for i in self.vertices:
        print(__UpperCAmelCase  ,					' : '  ,					' -> '.join([str(__UpperCAmelCase						) for j in self.vertices[i]]						)						)
  def 							lowercase_     (						self  ,					__UpperCAmelCase  ,					__UpperCAmelCase						)				->					None:
     if from_vertex in self.vertices:
        self.vertices[from_vertex].append(__UpperCAmelCase						)
     else:
        a   :	List[str]						=    [to_vertex]






  def 							lowercase_     (						self  ,					__UpperCAmelCase						)				->					set[int]:
     a   :	Union[str, Any]						=    set()

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

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

     while not queue.empty():
        a   :	int						=    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(__UpperCAmelCase						)
              visited.add(__UpperCAmelCase						)
     return visited


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

 testmod(verbose=True)

 SCREAMING_SNAKE_CASE__				:  Dict						= 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]









"""simple docstring"""






import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property


class 	A_       (     unittest.TestCase   ):





  """simple docstring"""

  @cached_property
  def 							lowercase_     (						self						)				->					Optional[Any]:
     return BlenderbotTokenizer.from_pretrained('facebook/blenderbot-3B'						)
  @cached_property
  def 							lowercase_     (						self						)				->					Optional[int]:
     return BlenderbotTokenizerFast.from_pretrained('facebook/blenderbot-3B'						)
  def 							lowercase_     (						self						)				->					Union[str, Any]:
     a   :	List[Any]						=    self.tokenizer_ab
     a   :	int						=    ' I am a small frog.'
     a   :	Any						=    tok([src_text]  ,					padding=__UpperCAmelCase  ,					truncation=__UpperCAmelCase						)['input_ids']
     a   :	List[str]						=    tok.batch_decode(__UpperCAmelCase  ,					skip_special_tokens=__UpperCAmelCase  ,					clean_up_tokenization_spaces=__UpperCAmelCase						)[0]
     assert src_text == decoded
  def 							lowercase_     (						self						)				->					Optional[Any]:
     a   :	Optional[int]						=    self.rust_tokenizer_ab
     a   :	List[Any]						=    ' I am a small frog.'
     a   :	Union[str, Any]						=    tok([src_text]  ,					padding=__UpperCAmelCase  ,					truncation=__UpperCAmelCase						)['input_ids']
     a   :	Optional[Any]						=    tok.batch_decode(__UpperCAmelCase  ,					skip_special_tokens=__UpperCAmelCase  ,					clean_up_tokenization_spaces=__UpperCAmelCase						)[0]
     assert src_text == decoded
  def 							lowercase_     (						self						)				->					Tuple:
     assert self.tokenizer_ab.add_prefix_space
     assert self.tokenizer_ab([' Sam', 'Sam']						).input_ids == [[55_02, 2], [55_02, 2]]






  def 							lowercase_     (						self						)				->					Tuple:
     assert self.rust_tokenizer_ab.add_prefix_space
     assert self.rust_tokenizer_ab([' Sam', 'Sam']						).input_ids == [[55_02, 2], [55_02, 2]]





