




'''simple docstring'''


import requests
from bsa import BeautifulSoup


def 						SCREAMING_SNAKE_CASE       (      a_	:							str = "AAPL"			):
  __a			=					f"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"
  __a			=					BeautifulSoup(requests.get(a_			).text				,					'html.parser'			)
  __a			=					'My(6px) Pos(r) smartphone_Mt(6px)'
  return soup.find('div'				,					class_=class_			).find('span'			).text


if __name__ == "__main__":
  for symbol in "AAPL AMZN IBM GOOG MSFT ORCL".split():
    print(f"""Current {symbol:<4} stock price is {stock_price(symbol):>8}""")









'''simple docstring'''


import torch

from diffusers import StableDiffusionPipeline


UpperCAmelCase_ 		=      "path-to-your-trained-model"
UpperCAmelCase_ 		=      StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("cuda")

UpperCAmelCase_ 		=      "A photo of sks dog in a bucket"
UpperCAmelCase_ 		=      pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

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



