





'''simple docstring'''

from dataclasses import asdict, dataclass
from typing import Optional

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


a        =						logging.get_logger(__name__)

# TODO Update this
a        =						{
    "facebook/esm-1b": "https://huggingface.co/facebook/esm-1b/resolve/main/config.json",
    # See all ESM models at https://huggingface.co/models?filter=esm
}







class __a (   _snake_case			):
   __UpperCamelCase   : Any	      =	'esm'





   def __init__(					self				:			Tuple				,lowerCamelCase				:			Optional[Any]=None				,lowerCamelCase				:			int=None				,lowerCamelCase				:			int=None				,lowerCamelCase				:			Optional[Any]=768				,lowerCamelCase				:			List[str]=12				,lowerCamelCase				:			Optional[int]=12				,lowerCamelCase				:			Union[str, Any]=3072				,lowerCamelCase				:			List[str]=0.1				,lowerCamelCase				:			List[str]=0.1				,lowerCamelCase				:			List[str]=1026				,lowerCamelCase				:			int=0.02				,lowerCamelCase				:			Any=1E-1_2				,lowerCamelCase				:			Dict="absolute"				,lowerCamelCase				:			Dict=True				,lowerCamelCase				:			Union[str, Any]=None				,lowerCamelCase				:			List[Any]=False				,lowerCamelCase				:			int=False				,lowerCamelCase				:			int=None				,lowerCamelCase				:			Union[str, Any]=None				,**lowerCamelCase				:			List[Any]				,):

      '''simple docstring'''

      super().__init__(pad_token_id=lowerCamelCase				,mask_token_id=lowerCamelCase				,**lowerCamelCase    )

      __SCREAMING_SNAKE_CASE      							=       vocab_size
      __SCREAMING_SNAKE_CASE      							=       hidden_size
      __SCREAMING_SNAKE_CASE      							=       num_hidden_layers
      __SCREAMING_SNAKE_CASE      							=       num_attention_heads
      __SCREAMING_SNAKE_CASE      							=       intermediate_size
      __SCREAMING_SNAKE_CASE      							=       hidden_dropout_prob
      __SCREAMING_SNAKE_CASE      							=       attention_probs_dropout_prob
      __SCREAMING_SNAKE_CASE      							=       max_position_embeddings
      __SCREAMING_SNAKE_CASE      							=       initializer_range
      __SCREAMING_SNAKE_CASE      							=       layer_norm_eps
      __SCREAMING_SNAKE_CASE      							=       position_embedding_type
      __SCREAMING_SNAKE_CASE      							=       use_cache
      __SCREAMING_SNAKE_CASE      							=       emb_layer_norm_before
      __SCREAMING_SNAKE_CASE      							=       token_dropout
      __SCREAMING_SNAKE_CASE      							=       is_folding_model
      if is_folding_model:
         if esmfold_config is None:
            logger.info("""No esmfold_config supplied for folding model, using default values."""    )
            __SCREAMING_SNAKE_CASE      							=       EsmFoldConfig()
         elif isinstance(lowerCamelCase				,lowerCamelCase    ):
            __SCREAMING_SNAKE_CASE      							=       EsmFoldConfig(**lowerCamelCase    )
         __SCREAMING_SNAKE_CASE      							=       esmfold_config
         if vocab_list is None:
            logger.warning("""No vocab_list supplied for folding model, assuming the ESM-2 vocabulary!"""    )
            __SCREAMING_SNAKE_CASE      							=       get_default_vocab_list()
         else:
            __SCREAMING_SNAKE_CASE      							=       vocab_list
      else:
         __SCREAMING_SNAKE_CASE      							=       None
         __SCREAMING_SNAKE_CASE      							=       None
      if self.esmfold_config is not None and getattr(self.esmfold_config				,"""use_esm_attn_map"""				,lowerCamelCase    ):
         raise ValueError("""The HuggingFace port of ESMFold does not support use_esm_attn_map at this time!"""    )





   def      UpperCAmelCase__     (					self				:			Any    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       super().to_dict()
      if isinstance(self.esmfold_config				,lowerCamelCase    ):
         __SCREAMING_SNAKE_CASE      							=       self.esmfold_config.to_dict()
      return output







@dataclass
class __a :
   __UpperCamelCase   : str	      =	None
   __UpperCamelCase   : bool	      =	True
   __UpperCamelCase   : bool	      =	False
   __UpperCamelCase   : bool	      =	False
   __UpperCamelCase   : bool	      =	False
   __UpperCamelCase   : float	      =	0

   __UpperCamelCase   : bool	      =	True
   __UpperCamelCase   : bool	      =	False

   __UpperCamelCase   : int	      =	128
   __UpperCamelCase   : "TrunkConfig"	      =	None





   def      UpperCAmelCase__     (					self				:			str    ):

      '''simple docstring'''

      if self.trunk is None:
         __SCREAMING_SNAKE_CASE      							=       TrunkConfig()
      elif isinstance(self.trunk				,lowerCamelCase    ):
         __SCREAMING_SNAKE_CASE      							=       TrunkConfig(**self.trunk    )





   def      UpperCAmelCase__     (					self				:			Optional[Any]    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       asdict(self    )
      __SCREAMING_SNAKE_CASE      							=       self.trunk.to_dict()
      return output







@dataclass
class __a :
   __UpperCamelCase   : int	      =	48
   __UpperCamelCase   : int	      =	1024
   __UpperCamelCase   : int	      =	128
   __UpperCamelCase   : int	      =	32
   __UpperCamelCase   : int	      =	32
   __UpperCamelCase   : int	      =	32
   __UpperCamelCase   : float	      =	0
   __UpperCamelCase   : float	      =	0
   __UpperCamelCase   : bool	      =	False
   __UpperCamelCase   : int	      =	4
   __UpperCamelCase   : Optional[int]	      =	128
   __UpperCamelCase   : "StructureModuleConfig"	      =	None





   def      UpperCAmelCase__     (					self				:			Optional[Any]    ):

      '''simple docstring'''

      if self.structure_module is None:
         __SCREAMING_SNAKE_CASE      							=       StructureModuleConfig()
      elif isinstance(self.structure_module				,lowerCamelCase    ):
         __SCREAMING_SNAKE_CASE      							=       StructureModuleConfig(**self.structure_module    )

      if self.max_recycles <= 0:
         raise ValueError(f"""`max_recycles` should be positive, got {self.max_recycles}."""    )
      if self.sequence_state_dim % self.sequence_state_dim != 0:
         raise ValueError(
             """`sequence_state_dim` should be a round multiple of `sequence_state_dim`, got"""
             f""" {self.sequence_state_dim} and {self.sequence_state_dim}."""    )
      if self.pairwise_state_dim % self.pairwise_state_dim != 0:
         raise ValueError(
             """`pairwise_state_dim` should be a round multiple of `pairwise_state_dim`, got"""
             f""" {self.pairwise_state_dim} and {self.pairwise_state_dim}."""    )

      __SCREAMING_SNAKE_CASE      							=       self.sequence_state_dim // self.sequence_head_width
      __SCREAMING_SNAKE_CASE      							=       self.pairwise_state_dim // self.pairwise_head_width

      if self.sequence_state_dim != sequence_num_heads * self.sequence_head_width:
         raise ValueError(
             """`sequence_state_dim` should be equal to `sequence_num_heads * sequence_head_width, got"""
             f""" {self.sequence_state_dim} != {sequence_num_heads} * {self.sequence_head_width}."""    )
      if self.pairwise_state_dim != pairwise_num_heads * self.pairwise_head_width:
         raise ValueError(
             """`pairwise_state_dim` should be equal to `pairwise_num_heads * pairwise_head_width, got"""
             f""" {self.pairwise_state_dim} != {pairwise_num_heads} * {self.pairwise_head_width}."""    )
      if self.pairwise_state_dim % 2 != 0:
         raise ValueError(f"""`pairwise_state_dim` should be even, got {self.pairwise_state_dim}."""    )

      if self.dropout >= 0.4:
         raise ValueError(f"""`dropout` should not be greater than 0.4, got {self.dropout}."""    )





   def      UpperCAmelCase__     (					self				:			Dict    ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE      							=       asdict(self    )
      __SCREAMING_SNAKE_CASE      							=       self.structure_module.to_dict()
      return output







@dataclass
class __a :
   __UpperCamelCase   : int	      =	384
   __UpperCamelCase   : int	      =	128
   __UpperCamelCase   : int	      =	16
   __UpperCamelCase   : int	      =	128
   __UpperCamelCase   : int	      =	12
   __UpperCamelCase   : int	      =	4
   __UpperCamelCase   : int	      =	8
   __UpperCamelCase   : float	      =	0.1
   __UpperCamelCase   : int	      =	8
   __UpperCamelCase   : int	      =	1
   __UpperCamelCase   : int	      =	2
   __UpperCamelCase   : int	      =	7
   __UpperCamelCase   : int	      =	10
   __UpperCamelCase   : float	      =	1E-8
   __UpperCamelCase   : float	      =	1E5





   def      UpperCAmelCase__     (					self				:			int    ):

      '''simple docstring'''

      return asdict(self    )





def 						__magic_name__       (							)						->					List[Any]:

   '''simple docstring'''







   return (
       "<cls>",
       "<pad>",
       "<eos>",
       "<unk>",
       "L",
       "A",
       "G",
       "V",
       "S",
       "E",
       "R",
       "T",
       "I",
       "D",
       "P",
       "K",
       "Q",
       "N",
       "F",
       "Y",
       "M",
       "H",
       "W",
       "C",
       "X",
       "B",
       "U",
       "Z",
       "O",
       ".",
       "-",
       "<null_1>",
       "<mask>",
   )












'''simple docstring'''

import requests
from bsa import BeautifulSoup

def 						__magic_name__       (							__UpperCAmelCase							,	__UpperCAmelCase      )						->					str:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE      							=       BeautifulSoup(requests.get(__UpperCAmelCase							,	params=__UpperCAmelCase      ).content							,	"""html.parser"""      )
   __SCREAMING_SNAKE_CASE      							=       soup.find("""div"""							,	attrs={"""class""": """gs_ri"""}      )
   __SCREAMING_SNAKE_CASE      							=       div.find("""div"""							,	attrs={"""class""": """gs_fl"""}      ).find_all("""a"""      )
   return anchors[2].get_text()


if __name__ == "__main__":
    a        =						{
        "title": (
            "Precisely geometry controlled microsupercapacitors for ultrahigh areal "
            "capacitance, volumetric capacitance, and energy density"
        ),
        "journal": "Chem. Mater.",
        "volume": 30,
        "pages": "3979-3990",
        "year": 2018,
        "hl": "en",
    }
    print(get_citation("https://scholar.google.com/scholar_lookup", params=params))





