

from itertools import product


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		int = 15							):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_						=    0.0
    SCREAMING_SNAKE_CASE_						=    42
    SCREAMING_SNAKE_CASE_						=    42
    SCREAMING_SNAKE_CASE_						=    42
    SCREAMING_SNAKE_CASE_						=    42
    SCREAMING_SNAKE_CASE_						=    42
    SCREAMING_SNAKE_CASE_						=    42

    for series in product(range(2							)			, repeat=_SCREAMING_SNAKE_CASE							):
        SCREAMING_SNAKE_CASE_						=    series.count(1							)
        SCREAMING_SNAKE_CASE_						=    num_turns - num_blue
        if num_red >= num_blue:
            continue
        SCREAMING_SNAKE_CASE_						=    1.0
        for ind, col in enumerate(_SCREAMING_SNAKE_CASE			, 2							):
            if col == 0:
                prob *= (ind - 1) / ind
            else:
                prob *= 1 / ind

        total_prob += prob

    return int(1 / total_prob							)


if __name__ == "__main__":
       print(F'{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							)


