



"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


A:     List[str]										=	logging.get_logger(__name__)

A:     List[str]										=	{
    "microsoft/resnet-50": "https://huggingface.co/microsoft/resnet-50/blob/main/config.json",
}



class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__   ,    UpperCAmelCase__				):
   __lowerCAmelCase						:     List[Any]		=		'resnet'
   __lowerCAmelCase						:     Optional[int]		=		['basic', 'bottleneck']

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE=3   ,  _SCREAMING_SNAKE_CASE=64   ,  _SCREAMING_SNAKE_CASE=[256, 512, 1024, 2048]   ,  _SCREAMING_SNAKE_CASE=[3, 4, 6, 3]   ,  _SCREAMING_SNAKE_CASE="bottleneck"   ,  _SCREAMING_SNAKE_CASE="relu"   ,  _SCREAMING_SNAKE_CASE=False   ,  _SCREAMING_SNAKE_CASE=None   ,  _SCREAMING_SNAKE_CASE=None   ,  **_SCREAMING_SNAKE_CASE   ,  )						->   Dict:





    '''simple docstring'''




    super().__init__(**_SCREAMING_SNAKE_CASE		)
    if layer_type not in self.layer_types:
     raise ValueError(F"layer_type={layer_type} is not one of {','.join(self.layer_types		)}"		)
    UpperCAmelCase			:      int			=			num_channels
    UpperCAmelCase			:      int			=			embedding_size
    UpperCAmelCase			:      Any			=			hidden_sizes
    UpperCAmelCase			:      str			=			depths
    UpperCAmelCase			:      Optional[int]			=			layer_type
    UpperCAmelCase			:      Optional[Any]			=			hidden_act
    UpperCAmelCase			:      int			=			downsample_in_first_stage
    UpperCAmelCase			:      Tuple			=			["""stem"""] + [F"stage{idx}" for idx in range(1   ,  len(_SCREAMING_SNAKE_CASE		) + 1		)]
    UpperCAmelCase			:      int			=			get_aligned_output_features_output_indices(
        out_features=_SCREAMING_SNAKE_CASE   ,  out_indices=_SCREAMING_SNAKE_CASE   ,  stage_names=self.stage_names		)



class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__				):
   __lowerCAmelCase						:     List[Any]		=		version.parse('1.11'				)

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Mapping[str, Mapping[int, str]]:





    '''simple docstring'''




    return OrderedDict(
        [
            ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
        ]		)




   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   float:





    '''simple docstring'''




    return 1E-3





"""simple docstring"""
import requests
from bsa import BeautifulSoup

def    _snake_case		(		UpperCamelCase		:	str = "AAPL"		):
 UpperCAmelCase			:      Any			=			F"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"
 UpperCAmelCase			:      Optional[int]			=			BeautifulSoup(requests.get(UpperCamelCase		).text    ,	"""html.parser"""		)
 UpperCAmelCase			:      int			=			"""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}""")
