'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase    :     int         =       {
    '''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase    :     List[str]         =       [
       '''MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''MegatronBertForCausalLM''',
       '''MegatronBertForMaskedLM''',
       '''MegatronBertForMultipleChoice''',
       '''MegatronBertForNextSentencePrediction''',
       '''MegatronBertForPreTraining''',
       '''MegatronBertForQuestionAnswering''',
       '''MegatronBertForSequenceClassification''',
       '''MegatronBertForTokenClassification''',
       '''MegatronBertModel''',
       '''MegatronBertPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_megatron_bert import (
          MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          MegatronBertForCausalLM,
          MegatronBertForMaskedLM,
          MegatronBertForMultipleChoice,
          MegatronBertForNextSentencePrediction,
          MegatronBertForPreTraining,
          MegatronBertForQuestionAnswering,
          MegatronBertForSequenceClassification,
          MegatronBertForTokenClassification,
          MegatronBertModel,
          MegatronBertPreTrainedModel,
      )

else:
   import sys

   _UpperCAmelCase    :     str         =       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)










'''simple docstring'''




import requests
from bsa import BeautifulSoup




def 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_							)   ->str:
	snake_case__	       =   BeautifulSoup(requests.get(UpperCAmelCase_					,				params=UpperCAmelCase_							).content					,				'html.parser'							)
	snake_case__	       =   soup.find('div'					,				attrs={'class': 'gs_ri'}							)
	snake_case__	       =   div.find('div'					,				attrs={'class': 'gs_fl'}							).find_all('a'							)
	return anchors[2].get_text()


if __name__ == "__main__":
			a__					:			int          =     {
			    '''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))



