


"""simple docstring"""






import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
						lowerCAmelCase__						:						Tuple		  =			'%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('Search: ')))

						print('Googling.....')

						lowerCAmelCase__						:						Tuple		  =			F"""https://www.google.com/search?q={query}&num=100"""

						lowerCAmelCase__						:						Union[str, Any]		  =			requests.get(
						    url,
						    headers={'User-Agent': str(UserAgent().random)},
						)

						try:
												lowerCAmelCase__						:						Dict		  =			(
												    BeautifulSoup(res.text, 'html.parser')
												    .find('div', attrs={'class': 'yuRUbf'})
												    .find('a')
												    .get('href')
												)

						except AttributeError:
												lowerCAmelCase__						:						List[Any]		  =			parse_qs(
												    BeautifulSoup(res.text, 'html.parser')
												    .find('div', attrs={'class': 'kCrYT'})
												    .find('a')
												    .get('href')
												)['url'][0]

						webbrowser.open(link)




"""simple docstring"""






import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


lowerCAmelCase__						:						Optional[int]		  =			False
class        snake_case (				unittest.TestCase       ):




					"""simple docstring"""

					pass






@slow
@require_torch_gpu
class        snake_case (				unittest.TestCase       ):




					"""simple docstring"""

					def 	__lowerCAmelCase		(       self     :			Tuple    ):
									UpperCAmelCase__    =							VersatileDiffusionImageVariationPipeline.from_pretrained('shi-labs/versatile-diffusion'    )
									pipe.to(lowerCamelCase__    )
									pipe.set_progress_bar_config(disable=lowerCamelCase__    )

									UpperCAmelCase__    =							load_image(
									    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'    )
									UpperCAmelCase__    =							torch.manual_seed(0    )
									UpperCAmelCase__    =							pipe(
									    image=lowerCamelCase__					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=50					,output_type='numpy'					,).images

									UpperCAmelCase__    =							image[0, 253:256, 253:256, -1]

									assert image.shape == (1, 512, 512, 3)
									UpperCAmelCase__    =							np.array([0.0_4_4_1, 0.0_4_6_9, 0.0_5_0_7, 0.0_5_7_5, 0.0_6_3_2, 0.0_6_5_0, 0.0_8_6_5, 0.0_9_0_9, 0.0_9_4_5]    )

									assert np.abs(image_slice.flatten() - expected_slice    ).max() < 1e-2



