

def 				__a							(       __A						):
    if not isinstance(__A			,							__A						):
        raise ValueError("Input series is not valid, valid series - [1, 2/3, 2]"						)
    if len(__A						) == 0:
        raise ValueError("Input list must be a non empty list"						)
    if len(__A						) == 1 and series[0] != 0:
        return True
    SCREAMING_SNAKE_CASE__         =    []
    SCREAMING_SNAKE_CASE__         =    len(__A						)
    for i in range(0			,							__A						):
        if series[i] == 0:
            raise ValueError("Input series cannot have 0 as an element"						)
        rec_series.append(1 / series[i]						)
    SCREAMING_SNAKE_CASE__         =    rec_series[1] - rec_series[0]
    for index in range(2			,							__A						):
        if rec_series[index] - rec_series[index - 1] != common_diff:
            return False
    return True





def 				__a							(       __A						):
    if not isinstance(__A			,							__A						):
        raise ValueError("Input series is not valid, valid series - [2, 4, 6]"						)
    if len(__A						) == 0:
        raise ValueError("Input list must be a non empty list"						)
    SCREAMING_SNAKE_CASE__         =    0
    for val in series:
        answer += 1 / val
    return len(__A						) / answer


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						)


