

import itertools


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		Optional[Any]							):





    """simple docstring"""


    return (
        int(''.join(combination[0:2]							)							) * int(''.join(combination[2:5]							)							)
        == int(''.join(combination[5:9]							)							)
    ) or (
        int(''.join(combination[0]							)							) * int(''.join(combination[1:5]							)							)
        == int(''.join(combination[5:9]							)							)
    )


def        _UpperCAmelCase							(	):





    """simple docstring"""


    return sum(
        {
            int(''.join(pandigital[5:9]							)							)
            for pandigital in itertools.permutations('123456789'							)
            if is_combination_valid(_SCREAMING_SNAKE_CASE							)
        }							)


if __name__ == "__main__":
       print(solution())





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


UpperCamelCase__	:   int								=     [
    "AutomaticSpeechRecognition",
    "AudioClassification",
    "ImageClassification",
    "LanguageModeling",
    "QuestionAnsweringExtractive",
    "Summarization",
    "TaskTemplate",
    "TextClassification",
]

UpperCamelCase__	:   Any								=     get_logger(__name__)


UpperCamelCase__	:   Union[str, Any]								=     {
    AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
    AudioClassification.task: AudioClassification,
    ImageClassification.task: ImageClassification,
    LanguageModeling.task: LanguageModeling,
    QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
    Summarization.task: Summarization,
    TextClassification.task: TextClassification,
}


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		dict							):





    """simple docstring"""


    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(_SCREAMING_SNAKE_CASE							)}"""							)
        return None
    SCREAMING_SNAKE_CASE_						=    NAMEaTEMPLATE.get(_SCREAMING_SNAKE_CASE							)
    return template.from_dict(_SCREAMING_SNAKE_CASE							)


