




"""simple docstring"""

import requests
from bsa import BeautifulSoup






def 		_snake_case	(   _snake_case				:   str = "AAPL"				)       ->   str:






      '''simple docstring'''


      _A     =  F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
      _A     =  BeautifulSoup(requests.get(_snake_case				).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"""

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a							      =     logging.get_logger(__name__)

a							      =     {
    '''facebook/xmod-base''': '''https://huggingface.co/facebook/xmod-base/resolve/main/config.json''',
    '''facebook/xmod-large-prenorm''': '''https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json''',
    '''facebook/xmod-base-13-125k''': '''https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json''',
    '''facebook/xmod-base-30-125k''': '''https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json''',
    '''facebook/xmod-base-30-195k''': '''https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json''',
    '''facebook/xmod-base-60-125k''': '''https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json''',
    '''facebook/xmod-base-60-265k''': '''https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json''',
    '''facebook/xmod-base-75-125k''': '''https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json''',
    '''facebook/xmod-base-75-269k''': '''https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json''',
}





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	Optional[Any]     =      '''xmod'''

 def __init__(					self			:			str       ,				_UpperCAmelCase			:			Optional[Any]=30_522       ,				_UpperCAmelCase			:			Any=768       ,				_UpperCAmelCase			:			int=12       ,				_UpperCAmelCase			:			List[str]=12       ,				_UpperCAmelCase			:			Dict=3_072       ,				_UpperCAmelCase			:			Union[str, Any]="gelu"       ,				_UpperCAmelCase			:			Optional[int]=0.1       ,				_UpperCAmelCase			:			Tuple=0.1       ,				_UpperCAmelCase			:			List[str]=512       ,				_UpperCAmelCase			:			Dict=2       ,				_UpperCAmelCase			:			Optional[int]=0.02       ,				_UpperCAmelCase			:			Any=1E-1_2       ,				_UpperCAmelCase			:			Tuple=1       ,				_UpperCAmelCase			:			int=0       ,				_UpperCAmelCase			:			List[Any]=2       ,				_UpperCAmelCase			:			List[str]="absolute"       ,				_UpperCAmelCase			:			Tuple=True       ,				_UpperCAmelCase			:			Tuple=None       ,				_UpperCAmelCase			:			int=False       ,				_UpperCAmelCase			:			Union[str, Any]=2       ,				_UpperCAmelCase			:			List[Any]=False       ,				_UpperCAmelCase			:			Dict=True       ,				_UpperCAmelCase			:			List[str]=True       ,				_UpperCAmelCase			:			Tuple=("en_XX",)       ,				_UpperCAmelCase			:			List[str]=None       ,				**_UpperCAmelCase			:			Optional[Any]       ,				):
       super().__init__(pad_token_id=_UpperCAmelCase       ,				bos_token_id=_UpperCAmelCase       ,				eos_token_id=_UpperCAmelCase       ,				**_UpperCAmelCase						)

       _A     =  vocab_size
       _A     =  hidden_size
       _A     =  num_hidden_layers
       _A     =  num_attention_heads
       _A     =  hidden_act
       _A     =  intermediate_size
       _A     =  hidden_dropout_prob
       _A     =  attention_probs_dropout_prob
       _A     =  max_position_embeddings
       _A     =  type_vocab_size
       _A     =  initializer_range
       _A     =  layer_norm_eps
       _A     =  position_embedding_type
       _A     =  use_cache
       _A     =  classifier_dropout
       _A     =  pre_norm
       _A     =  adapter_reduction_factor
       _A     =  adapter_layer_norm
       _A     =  adapter_reuse_layer_norm
       _A     =  ln_before_adapter
       _A     =  list(_UpperCAmelCase						)
       _A     =  default_language





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''

 @property
 def      lowerCAmelCase_				(					self			:			Dict						):
       if self.task == "multiple-choice":
             _A     =  {0: 'batch', 1: 'choice', 2: 'sequence'}
       else:
             _A     =  {0: 'batch', 1: 'sequence'}
       return OrderedDict(
           [
               ('input_ids', dynamic_axis),
               ('attention_mask', dynamic_axis),
           ]						)

