


'''simple docstring'''



from typing import TYPE_CHECKING

import torch

from ..models.auto import AutoModelForVisualQuestionAnswering, AutoProcessor
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
  from PIL import Image


class 		_snake_case					(     a__	):
     lowerCAmelCase      :Any   =					'''dandelin/vilt-b32-finetuned-vqa'''
     lowerCAmelCase      :Optional[Any]   =					(
         '''This is a tool that answers a question about an image. It takes an input named `image` which should be the '''
         '''image containing the information, as well as a `question` which should be the question in English. It '''
         '''returns a text that is the answer to the question.'''
     )
     lowerCAmelCase      :Union[str, Any]   =					'''image_qa'''
     lowerCAmelCase      :Tuple   =					AutoProcessor
     lowerCAmelCase      :List[Any]   =					AutoModelForVisualQuestionAnswering

     lowerCAmelCase      :Dict   =					['''image''', '''text''']
     lowerCAmelCase      :List[str]   =					['''text''']




     def __init__(      self							,							*_lowerCamelCase							,							**_lowerCamelCase):
        requires_backends(self							,							["""vision"""])
        super().__init__(*_lowerCamelCase							,							**_lowerCamelCase)




     def 				snake_case__						(      self							,							_lowerCamelCase							,							_lowerCamelCase):
        return self.pre_processor(_lowerCamelCase							,							_lowerCamelCase							,							return_tensors="""pt""")




     def 				snake_case__						(      self							,							_lowerCamelCase):
        with torch.no_grad():
           return self.model(**_lowerCamelCase).logits




     def 				snake_case__						(      self							,							_lowerCamelCase):
        UpperCAmelCase__  :					Tuple        =     outputs.argmax(-1).item()
        return self.model.config.idalabel[idx]



'''simple docstring'''



from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean







def     _UpperCamelCase      (		UpperCamelCase__					):

			# A local function to see if a dot lands in the circle.
			def is_in_circle(UpperCamelCase__ ,      UpperCamelCase__					) -> bool:
						UpperCAmelCase__  :					List[str]        =     sqrt((x**2) + (y**2)					)
						# Our circle has a radius of 1, so a distance
						# greater than 1 would land outside the circle.
						return distance_from_centre <= 1

			# The proportion of guesses that landed in the circle
			UpperCAmelCase__  :					Optional[Any]        =     mean(
			    int(is_in_circle(uniform(-1.0 ,      1.0					) ,      uniform(-1.0 ,      1.0					)					)					)
			    for _ in range(UpperCamelCase__					)					)
			# The ratio of the area for circle to square is pi/4.
			UpperCAmelCase__  :					int        =     proportion * 4
			print(f'''The estimated value of pi is {pi_estimate}'''					)
			print(f'''The numpy value of pi is {pi}'''					)
			print(f'''The total error is {abs(pi - pi_estimate					)}'''					)







def     _UpperCamelCase      (		UpperCamelCase__ ,      UpperCamelCase__ ,      UpperCamelCase__ = 0.0 ,      UpperCamelCase__ = 1.0 ,      ):
			return mean(
			    function_to_integrate(uniform(UpperCamelCase__ ,      UpperCamelCase__					)					) for _ in range(UpperCamelCase__					)					) * (max_value - min_value)







def     _UpperCamelCase      (		UpperCamelCase__ ,      UpperCamelCase__ = 0.0 ,      UpperCamelCase__ = 1.0					):

			def identity_function(UpperCamelCase__					) -> float:
						return x

			UpperCAmelCase__  :					List[str]        =     area_under_curve_estimator(
			    UpperCamelCase__ ,      UpperCamelCase__ ,      UpperCamelCase__ ,      UpperCamelCase__					)
			UpperCAmelCase__  :					Optional[int]        =     (max_value * max_value - min_value * min_value) / 2

			print("""******************"""					)
			print(f'''Estimating area under y=x where x varies from {min_value} to {max_value}'''					)
			print(f'''Estimated value is {estimated_value}'''					)
			print(f'''Expected value is {expected_value}'''					)
			print(f'''Total error is {abs(estimated_value - expected_value					)}'''					)
			print("""******************"""					)







def     _UpperCamelCase      (		UpperCamelCase__					):

			def function_to_integrate(UpperCamelCase__					) -> float:
						return sqrt(4.0 - x * x					)

			UpperCAmelCase__  :					Dict        =     area_under_curve_estimator(
			    UpperCamelCase__ ,      UpperCamelCase__ ,      0.0 ,      2.0					)

			print("""******************"""					)
			print("""Estimating pi using area_under_curve_estimator"""					)
			print(f'''Estimated value is {estimated_value}'''					)
			print(f'''Expected value is {pi}'''					)
			print(f'''Total error is {abs(estimated_value - pi					)}'''					)
			print("""******************"""					)


if __name__ == "__main__":
		import doctest

		doctest.testmod()