

import random



class    __snake_case	:

  def __init__(       self    ,		_A    ,		_A):
      SCREAMING_SNAKE_CASE_						=    x
      SCREAMING_SNAKE_CASE_						=    y

  def     lowerCAmelCase__  (       self):
      return (self.x**2 + self.y**2) <= 1


  @classmethod
  def     lowerCAmelCase__  (       cls):
      return cls(x=random.random()    ,		y=random.random())






def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		int							):





    """simple docstring"""


    if number_of_simulations < 1:
        raise ValueError('At least one simulation is necessary to estimate PI.'							)

    SCREAMING_SNAKE_CASE_						=    0
    for _ in range(_SCREAMING_SNAKE_CASE							):
        SCREAMING_SNAKE_CASE_						=    Point.random_unit_square()

        if random_point.is_in_unit_circle():
            number_in_unit_circle += 1

    return 4 * number_in_unit_circle / number_of_simulations


if __name__ == "__main__":
       # import doctest

       # doctest.testmod()
       from math import pi

       UpperCamelCase__	:   Tuple								=     "Please enter the desired number of Monte Carlo simulations: "
       UpperCamelCase__	:   List[Any]								=     estimate_pi(int(input(prompt).strip()))
       print(F'An estimate of PI is {my_pi} with an error of {abs(my_pi - pi)}')





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							)


