

lowerCAmelCase__							=			{
    "+": lambda x, y: x + y,
    "-": lambda x, y: x - y,
    "*": lambda x, y: x * y,
    "/": lambda x, y: x / y,
}
def   _lowerCAmelCase(						__A      ):
  return c.isdigit()
def   _lowerCAmelCase(						__A      ):
  UpperCAmelCase          =	[]

  # iterate over the string in reverse order
  for c in expression.split()[::-1]:
    # push operand to stack
    if is_operand(__A      ):
      stack.append(int(__A      )      )

    else:
      # pop values from stack can calculate the result
      # push the result onto the stack again
      UpperCAmelCase          =	stack.pop()
      UpperCAmelCase          =	stack.pop()
      stack.append(calc[c](__A ,							__A      )      )

  return stack.pop()


# Driver code
if __name__ == "__main__":
      lowerCAmelCase__							=			"+ 9 * 2 6"
      print(evaluate(test_expression))

      lowerCAmelCase__							=			"/ * 10 2 + 4 1 "
      print(evaluate(test_expression))






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						)


