

from __future__ import annotations







class  UpperCamelCase_      :


  """simple docstring"""



  def __init__(						self     :					int  ,	A_     :					int						)       ->			None:
      SCREAMING_SNAKE_CASE__         =    value
      SCREAMING_SNAKE_CASE__         =    None
      SCREAMING_SNAKE_CASE__         =    None







class  UpperCamelCase_      :


  """simple docstring"""
  SCREAMING_SNAKE_CASE__					:			int



  def __init__(						self     :					str						)       ->			None:
      SCREAMING_SNAKE_CASE__         =    0



  def   _UpperCamelCase     (						self     :					List[Any]  ,	A_     :					Node | None  ,	A_     :					int						)       ->			None:
      if node is None:
          return

      if path_sum == self.target:
          self.paths += 1

      if node.left:
          self.depth_first_search(node.left  ,	path_sum + node.left.value						)
      if node.right:
          self.depth_first_search(node.right  ,	path_sum + node.right.value						)







  def   _UpperCamelCase     (						self     :					Dict  ,	A_     :					Node | None  ,	A_     :					int | None = None						)       ->			int:
      if node is None:
          return 0
      if target is not None:
          SCREAMING_SNAKE_CASE__         =    target

      self.depth_first_search(A_  ,	node.value						)
      self.path_sum(node.left						)
      self.path_sum(node.right						)

      return self.paths


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


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

A__										=      get_logger(__name__)


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





def 				__a							(       __A						):
    SCREAMING_SNAKE_CASE__         =    task_template_dict.get("task"						)
    if task_name is None:
        logger.warning(f"Couldn't find template for task '{task_name}'. Available templates: {list(__A						)}"						)
        return None
    SCREAMING_SNAKE_CASE__         =    NAMEaTEMPLATE.get(__A						)
    return template.from_dict(__A						)


