






"""simple docstring"""




import requests
from bsa import BeautifulSoup





def 						UpperCAmelCase__		(					_UpperCAmelCase			, _UpperCAmelCase ):






  """simple docstring"""





  A_  :	Optional[int]    						=  (
      'https://www.horoscope.com/us/horoscopes/general/'
      f"""horoscope-general-daily-{day}.aspx?sign={zodiac_sign}"""
  )
  A_  :	List[str]    						=  BeautifulSoup(requests.get(_UpperCAmelCase ).content			, 'html.parser' )
  return soup.find('div'			, class_='main-horoscope' ).p.text


if __name__ == "__main__":
   print('Daily Horoscope. \n')
   print(
       'enter your Zodiac sign number:\n',
       '1. Aries\n',
       '2. Taurus\n',
       '3. Gemini\n',
       '4. Cancer\n',
       '5. Leo\n',
       '6. Virgo\n',
       '7. Libra\n',
       '8. Scorpio\n',
       '9. Sagittarius\n',
       '10. Capricorn\n',
       '11. Aquarius\n',
       '12. Pisces\n',
   )
   lowerCamelCase_					:						str      = int(input('number> ').strip())
   print('choose some day:\n', 'yesterday\n', 'today\n', 'tomorrow\n')
   lowerCamelCase_					:						Optional[Any]      = input('enter the day> ')
   lowerCamelCase_					:						Union[str, Any]      = horoscope(zodiac_sign, day)
   print(horoscope_text)






"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


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

lowerCamelCase_					:						Optional[int]      = {
    'google/electra-small-generator': 'https://huggingface.co/google/electra-small-generator/resolve/main/config.json',
    'google/electra-base-generator': 'https://huggingface.co/google/electra-base-generator/resolve/main/config.json',
    'google/electra-large-generator': 'https://huggingface.co/google/electra-large-generator/resolve/main/config.json',
    'google/electra-small-discriminator': (
        'https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'
    ),
    'google/electra-base-discriminator': (
        'https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'
    ),
    'google/electra-large-discriminator': (
        'https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'
    ),
}

class 			_UpperCAmelCase  (       UpperCAmelCase__		):



      '''simple docstring'''
      lowercase_				:			Tuple        =       """electra"""

      def __init__(					self ,				snake_case_=3_0_5_2_2 ,				snake_case_=1_2_8 ,				snake_case_=2_5_6 ,				snake_case_=1_2 ,				snake_case_=4 ,				snake_case_=1_0_2_4 ,				snake_case_="gelu" ,				snake_case_=0.1 ,				snake_case_=0.1 ,				snake_case_=5_1_2 ,				snake_case_=2 ,				snake_case_=0.02 ,				snake_case_=1E-12 ,				snake_case_="first" ,				snake_case_=True ,				snake_case_="gelu" ,				snake_case_=0.1 ,				snake_case_=0 ,				snake_case_="absolute" ,				snake_case_=True ,				snake_case_=None ,				**snake_case_ ,				):

        """simple docstring"""

        super().__init__(pad_token_id=snake_case_ ,				**snake_case_  )

        A_  :	Optional[Any]    						=  vocab_size
        A_  :	Any    						=  embedding_size
        A_  :	Optional[int]    						=  hidden_size
        A_  :	Tuple    						=  num_hidden_layers
        A_  :	Tuple    						=  num_attention_heads
        A_  :	List[Any]    						=  intermediate_size
        A_  :	Any    						=  hidden_act
        A_  :	str    						=  hidden_dropout_prob
        A_  :	Any    						=  attention_probs_dropout_prob
        A_  :	str    						=  max_position_embeddings
        A_  :	Optional[Any]    						=  type_vocab_size
        A_  :	Dict    						=  initializer_range
        A_  :	Optional[int]    						=  layer_norm_eps

        A_  :	int    						=  summary_type
        A_  :	List[str]    						=  summary_use_proj
        A_  :	Optional[Any]    						=  summary_activation
        A_  :	Optional[Any]    						=  summary_last_dropout
        A_  :	List[Any]    						=  position_embedding_type
        A_  :	Union[str, Any]    						=  use_cache
        A_  :	Tuple    						=  classifier_dropout


class 			_UpperCAmelCase  (       UpperCAmelCase__		):



      '''simple docstring'''

      @property
      def  lowerCamelCase_      (					self  ):

        """simple docstring"""

        if self.task == "multiple-choice":
          A_  :	int    						=  {0: 'batch', 1: 'choice', 2: 'sequence'}
        else:
          A_  :	Optional[Any]    						=  {0: 'batch', 1: 'sequence'}
        return OrderedDict(
            [
                ('input_ids', dynamic_axis),
                ('attention_mask', dynamic_axis),
                ('token_type_ids', dynamic_axis),
            ]  )