
lowercase_											=	{0: [1, 2], 1: [0, 3], 2: [0], 3: [1], 4: [5, 6], 5: [4, 6], 6: [4, 5]}

lowercase_											=	{0: [1, 2, 3], 1: [0, 3], 2: [0], 3: [0, 1], 4: [], 5: []}


def     a__			(    snake_case   ,	snake_case   ,	snake_case    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					int			=						True
  __SCREAMING_SNAKE_CASE     :					Tuple			=						[]

  for neighbour in graph[vert]:
    if not visited[neighbour]:
      connected_verts += dfs(snake_case   ,	snake_case   ,	snake_case    )

  return [vert, *connected_verts]


def     a__			(    snake_case    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					List[str]			=						len(snake_case    )
  __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						graph_size * [False]
  __SCREAMING_SNAKE_CASE     :					Any			=						[]

  for i in range(snake_case    ):
    if not visited[i]:
      __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						dfs(snake_case   ,	snake_case   ,	snake_case    )
      components_list.append(snake_case    )

  return components_list


if __name__ == "__main__":
 import doctest

 doctest.testmod()


from typing import Optional

from ..utils.logging import get_logger
from .audio_classificiation import AudioClassification
from .automatic_speech_recognition import AutomaticSpeechRecognition
from .base import TaskTemplate
from .image_classification import ImageClassification
from .language_modeling import LanguageModeling
from .question_answering import QuestionAnsweringExtractive
from .summarization import Summarization
from .text_classification import TextClassification


lowercase_											=	[
    """AutomaticSpeechRecognition""",
    """AudioClassification""",
    """ImageClassification""",
    """LanguageModeling""",
    """QuestionAnsweringExtractive""",
    """Summarization""",
    """TaskTemplate""",
    """TextClassification""",
]

lowercase_											=	get_logger(__name__)


lowercase_											=	{
    AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
    AudioClassification.task: AudioClassification,
    ImageClassification.task: ImageClassification,
    LanguageModeling.task: LanguageModeling,
    QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
    Summarization.task: Summarization,
    TextClassification.task: TextClassification,
}


def     a__			(    snake_case    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					str			=						task_template_dict.get('''task'''    )
  if task_name is None:
    logger.warning(F'''Couldn\'t find template for task \'{task_name}\'. Available templates: {list(snake_case    )}'''    )
    return None
  __SCREAMING_SNAKE_CASE     :					Any			=						NAMEaTEMPLATE.get(snake_case    )
  return template.from_dict(snake_case    )
