import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


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

__lowerCAmelCase    :  Tuple										= {}
class 				lowerCamelCase			(							__snake_case					):
      __lowerCamelCase							=					'fsmt_decoder'






      def __init__(      self  ,		__lowerCamelCase=0  ,		__lowerCamelCase=0						)     ->				Optional[Any]:


          '''simple docstring'''







          super().__init__()
          snake_case:						Optional[Any]         =   vocab_size
          snake_case:						List[str]         =   bos_token_id





class 				lowerCamelCase			(							__snake_case					):
      __lowerCamelCase							=					'fsmt'
      __lowerCamelCase							=					{'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}






      def __init__(      self  ,		__lowerCamelCase=["en", "de"]  ,		__lowerCamelCase=4_20_24  ,		__lowerCamelCase=4_20_24  ,		__lowerCamelCase="relu"  ,		__lowerCamelCase=10_24  ,		__lowerCamelCase=2_00  ,		__lowerCamelCase=10_24  ,		__lowerCamelCase=40_96  ,		__lowerCamelCase=12  ,		__lowerCamelCase=16  ,		__lowerCamelCase=0.0  ,		__lowerCamelCase=40_96  ,		__lowerCamelCase=12  ,		__lowerCamelCase=16  ,		__lowerCamelCase=0.0  ,		__lowerCamelCase=0.0  ,		__lowerCamelCase=0.1  ,		__lowerCamelCase=0.0  ,		__lowerCamelCase=0.02  ,		__lowerCamelCase=2  ,		__lowerCamelCase=True  ,		__lowerCamelCase=True  ,		__lowerCamelCase=False  ,		__lowerCamelCase=5  ,		__lowerCamelCase=1.0  ,		__lowerCamelCase=False  ,		__lowerCamelCase=True  ,		__lowerCamelCase=1  ,		__lowerCamelCase=0  ,		__lowerCamelCase=2  ,		__lowerCamelCase=2  ,		**__lowerCamelCase  ,		)     ->				List[str]:


          '''simple docstring'''







          snake_case:						Optional[Any]         =   langs
          snake_case:						Tuple         =   src_vocab_size
          snake_case:						int         =   tgt_vocab_size
          snake_case:						List[str]         =   d_model  # encoder_embed_dim and decoder_embed_dim

          snake_case:						Optional[Any]         =   encoder_ffn_dim
          snake_case:						List[str]         =   encoder_layers
          snake_case:						str         =   encoder_attention_heads
          snake_case:						Optional[Any]         =   encoder_layerdrop
          snake_case:						Tuple         =   decoder_layerdrop
          snake_case:						Tuple         =   decoder_ffn_dim
          snake_case:						Dict         =   decoder_layers
          snake_case:						Any         =   decoder_attention_heads
          snake_case:						Tuple         =   max_position_embeddings
          snake_case:						Dict         =   init_std  # Normal(0, this parameter)
          snake_case:						List[str]         =   activation_function

          snake_case:						List[Any]         =   DecoderConfig(vocab_size=__lowerCamelCase  ,		bos_token_id=__lowerCamelCase						)
          if "decoder" in common_kwargs:
              del common_kwargs["decoder"]

          snake_case:						Optional[int]         =   scale_embedding  # scale factor will be sqrt(d_model) if True

          # 3 Types of Dropout
          snake_case:						Optional[int]         =   attention_dropout
          snake_case:						Optional[Any]         =   activation_dropout
          snake_case:						Dict         =   dropout

          snake_case:						List[Any]         =   use_cache
          super().__init__(
              pad_token_id=__lowerCamelCase  ,		bos_token_id=__lowerCamelCase  ,		eos_token_id=__lowerCamelCase  ,		decoder_start_token_id=__lowerCamelCase  ,		is_encoder_decoder=__lowerCamelCase  ,		tie_word_embeddings=__lowerCamelCase  ,		forced_eos_token_id=__lowerCamelCase  ,		max_length=__lowerCamelCase  ,		num_beams=__lowerCamelCase  ,		length_penalty=__lowerCamelCase  ,		early_stopping=__lowerCamelCase  ,		**__lowerCamelCase  ,		)






      def 			lowerCAmelCase_   (      self						)     ->				List[Any]:


          '''simple docstring'''







          snake_case:						Union[str, Any]         =   copy.deepcopy(self.__dict__						)
          snake_case:						str         =   self.decoder.to_dict()
          snake_case:						Union[str, Any]         =   self.__class__.model_type
          return output



from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

__lowerCAmelCase    :  Optional[int]										= 'https://www.wellrx.com/prescriptions/{0}/{1}/?freshSearch=true'

def   a_					(_lowerCAmelCase  :   str			,	_lowerCAmelCase  :   str       )->				list | None:

    try:
        # Has user provided both inputs?
        if not drug_name or not zip_code:
            return None

        snake_case:						List[str]         =   BASE_URL.format(_lowerCAmelCase			,	_lowerCAmelCase       )
        snake_case:						Optional[Any]         =   get(_lowerCAmelCase       )

        # Is the response ok?
        response.raise_for_status()

        # Scrape the data using bs4
        snake_case:						Tuple         =   BeautifulSoup(response.text			,	"""html.parser"""       )

        # This list will store the name and price.
        snake_case:						List[Any]         =   []

        # Fetch all the grids that contains the items.
        snake_case:						Any         =   soup.find_all("""div"""			,	{"""class""": """grid-x pharmCard"""}       )
        if grid_list and len(_lowerCAmelCase       ) > 0:
            for grid in grid_list:
                # Get the pharmacy price.
                snake_case:						Union[str, Any]         =   grid.find("""p"""			,	{"""class""": """list-title"""}       ).text

                # Get price of the drug.
                snake_case:						Optional[Any]         =   grid.find("""span"""			,	{"""p""", """price price-large"""}       ).text

                pharmacy_price_list.append(
                    {
                        """pharmacy_name""": pharmacy_name,
                        """price""": price,
                    }       )

        return pharmacy_price_list

    except (HTTPError, exceptions.RequestException, ValueError):
        return None


if __name__ == "__main__":
    # Enter a drug name and a zip code
    __lowerCAmelCase    :  Union[str, Any]										= input('Enter drug name: ').strip()
    __lowerCAmelCase    :  Tuple										= input('Enter zip code: ').strip()

    __lowerCAmelCase    :  list | None										= fetch_pharmacy_and_price_list(
        drug_name, zip_code
    )

    if pharmacy_price_list:
        print(F"""\nSearch results for {drug_name} at location {zip_code}:""")
        for pharmacy_price in pharmacy_price_list:
            __lowerCAmelCase    :  int										= pharmacy_price['pharmacy_name']
            __lowerCAmelCase    :  List[str]										= pharmacy_price['price']

            print(F"""Pharmacy: {name} Price: {price}""")
    else:
        print(F"""No results found for {drug_name}""")


