




import requests
from bsa import BeautifulSoup

def 			a   (_lowerCAmelCase = "AAPL"     ):
							SCREAMING_SNAKE_CASE_   	=    F"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"
							SCREAMING_SNAKE_CASE_   	=    BeautifulSoup(requests.get(_lowerCAmelCase     ).text  ,    '''html.parser'''     )
							SCREAMING_SNAKE_CASE_   	=    '''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}""")








import unittest

from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax

from .test_modeling_common_flax import FlaxModelTesterMixin


if is_flax_available():
			import jax






@require_flax
class  __magic_name__						(  __UpperCAmelCase    ,  unittest.TestCase):
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							str	      =					FlaxAutoencoderKL


				@property
				def     _A							(							self:   Any		):
											SCREAMING_SNAKE_CASE_   	=    4
											SCREAMING_SNAKE_CASE_   	=    3
											SCREAMING_SNAKE_CASE_   	=    (32, 32)

											SCREAMING_SNAKE_CASE_   	=    jax.random.PRNGKey(0		)
											SCREAMING_SNAKE_CASE_   	=    jax.random.uniform(_lowerCamelCase		,					((batch_size, num_channels) + sizes)		)

											return {"sample": image, "prng_key": prng_key}





				def     _A							(							self:   List[str]		):
											SCREAMING_SNAKE_CASE_   	=    {
											    '''block_out_channels''': [32, 64],
											    '''in_channels''': 3,
											    '''out_channels''': 3,
											    '''down_block_types''': ['''DownEncoderBlock2D''', '''DownEncoderBlock2D'''],
											    '''up_block_types''': ['''UpDecoderBlock2D''', '''UpDecoderBlock2D'''],
											    '''latent_channels''': 4,
											}
											SCREAMING_SNAKE_CASE_   	=    self.dummy_input
											return init_dict, inputs_dict


