"""simple docstring"""






import math
from collections.abc import Callable


def      UpperCAmelCase__			(							lowerCAmelCase__	:Callable[[float], float]   ,						lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float						)					->       float:
      '''simple docstring'''


      lowercase								=      xa
      lowercase								=      xa
      while True:
            if x_n == x_na or function(lowerCAmelCase__						) == function(lowerCAmelCase__						):
                  raise ZeroDivisionError("""float division by zero, could not find root"""						)
            lowercase								=      x_na - (
                function(lowerCAmelCase__						) / ((function(lowerCAmelCase__						) - function(lowerCAmelCase__						)) / (x_na - x_n))
            )
            if abs(x_na - x_na						) < 1_0**-5:
                  return x_na
            lowercase								=      x_na
            lowercase								=      x_na


def      UpperCAmelCase__			(							lowerCAmelCase__	:float						)					->       float:
      '''simple docstring'''


      return math.pow(lowerCAmelCase__   ,						3						) - (2 * x) - 5


if __name__ == "__main__":
       print(intersection(f, 3, 3.5))




"""simple docstring"""






import torch

from diffusers import StableDiffusionPipeline


__lowerCAmelCase       :			str   	="""path-to-your-trained-model"""
__lowerCAmelCase       :			int   	=StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")

__lowerCAmelCase       :			Optional[int]   	="""A photo of sks dog in a bucket"""
__lowerCAmelCase       :			int   	=pipe(prompt, num_inference_steps=5_0, guidance_scale=7.5).images[0]

image.save("""dog-bucket.png""")



