

'''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	 =     {
    '''nghuyong/ernie-1.0-base-zh''': '''https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json''',
    '''nghuyong/ernie-2.0-base-en''': '''https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json''',
    '''nghuyong/ernie-2.0-large-en''': '''https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-base-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-medium-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-mini-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-micro-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-nano-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json''',
    '''nghuyong/ernie-gram-zh''': '''https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json''',
    '''nghuyong/ernie-health-zh''': '''https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json''',
}






class 							A_				(	snake_case__      ):
     _lowercase    :  Dict          =			'ernie'


     def __init__(							self    :	Any    ,						UpperCAmelCase    :	Any=3_0_5_2_2    ,						UpperCAmelCase    :	Tuple=7_6_8    ,						UpperCAmelCase    :	Any=1_2    ,						UpperCAmelCase    :	Optional[Any]=1_2    ,						UpperCAmelCase    :	Any=3_0_7_2    ,						UpperCAmelCase    :	str="gelu"    ,						UpperCAmelCase    :	str=0.1    ,						UpperCAmelCase    :	Dict=0.1    ,						UpperCAmelCase    :	List[str]=5_1_2    ,						UpperCAmelCase    :	int=2    ,						UpperCAmelCase    :	List[Any]=3    ,						UpperCAmelCase    :	int=False    ,						UpperCAmelCase    :	Union[str, Any]=0.02    ,						UpperCAmelCase    :	str=1E-12    ,						UpperCAmelCase    :	List[Any]=0    ,						UpperCAmelCase    :	Dict="absolute"    ,						UpperCAmelCase    :	int=True    ,						UpperCAmelCase    :	List[Any]=None    ,						**UpperCAmelCase    :	List[str]    ,						)							->			str:
      super().__init__(pad_token_id=UpperCAmelCase    ,						**UpperCAmelCase      )

      __lowerCAmelCase:     List[Any]     			=   vocab_size
      __lowerCAmelCase:     Dict     			=   hidden_size
      __lowerCAmelCase:     List[Any]     			=   num_hidden_layers
      __lowerCAmelCase:     List[str]     			=   num_attention_heads
      __lowerCAmelCase:     List[Any]     			=   hidden_act
      __lowerCAmelCase:     Optional[int]     			=   intermediate_size
      __lowerCAmelCase:     Union[str, Any]     			=   hidden_dropout_prob
      __lowerCAmelCase:     Optional[int]     			=   attention_probs_dropout_prob
      __lowerCAmelCase:     List[str]     			=   max_position_embeddings
      __lowerCAmelCase:     Union[str, Any]     			=   type_vocab_size
      __lowerCAmelCase:     Dict     			=   task_type_vocab_size
      __lowerCAmelCase:     int     			=   use_task_id
      __lowerCAmelCase:     Any     			=   initializer_range
      __lowerCAmelCase:     Optional[Any]     			=   layer_norm_eps
      __lowerCAmelCase:     List[Any]     			=   position_embedding_type
      __lowerCAmelCase:     Optional[Any]     			=   use_cache
      __lowerCAmelCase:     Tuple     			=   classifier_dropout







class 							A_				(	snake_case__      ):


     @property
     def 						UpperCAmelCase						(							self    :	str      )							->			Mapping[str, Mapping[int, str]]:
      if self.task == "multiple-choice":
       __lowerCAmelCase:     str     			=   {0: 'batch', 1: 'choice', 2: 'sequence'}
      else:
       __lowerCAmelCase:     Dict     			=   {0: 'batch', 1: 'sequence'}
      return OrderedDict(
          [
              ('input_ids', dynamic_axis),
              ('attention_mask', dynamic_axis),
              ('token_type_ids', dynamic_axis),
              ('task_type_ids', dynamic_axis),
          ]      )








import requests
from bsa import BeautifulSoup







def _a				( SCREAMING_SNAKE_CASE	:    int					,      SCREAMING_SNAKE_CASE	:    str	)					->					str:

 """simple docstring"""






 __lowerCAmelCase:     Tuple     			=   (
     'https://www.horoscope.com/us/horoscopes/general/'
     f'''horoscope-general-daily-{day}.aspx?sign={zodiac_sign}'''
 )
 __lowerCAmelCase:     Optional[Any]     			=   BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE	).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''',
  )
  _a	 =     int(input('''number> ''').strip())
  print('''choose some day:\n''', '''yesterday\n''', '''today\n''', '''tomorrow\n''')
  _a	 =     input('''enter the day> ''')
  _a	 =     horoscope(zodiac_sign, day)
  print(horoscope_text)





