

def    lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							int = 3_0 )     -> int:




				'''simple docstring'''





				A__            =     exponent + 2
				A__            =     (1 + 5**0.5) / 2
				A__            =     (phi**fibonacci_index - (phi - 1) ** fibonacci_index) / 5**0.5

				return int(SCREAMING_SNAKE_CASE_ )


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


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

lowerCAmelCase__						=	get_logger(__name__)


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



def    lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							dict )     -> Optional[TaskTemplate]:




				'''simple docstring'''





				A__            =     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
				A__            =     NAMEaTEMPLATE.get(SCREAMING_SNAKE_CASE_ )
				return template.from_dict(SCREAMING_SNAKE_CASE_ )

