


'''simple docstring'''

import requests
from bsa import BeautifulSoup





def __snake_case					(      UpperCAmelCase_						:						str					,				UpperCAmelCase_						:						dict		):
 lowerCamelCase_      =  BeautifulSoup(requests.get(UpperCAmelCase_					,				params=UpperCAmelCase_		).content					,				"html.parser"		)
 lowerCamelCase_      =  soup.find("div"					,				attrs={"class": "gs_ri"}		)
 lowerCamelCase_      =  div.find("div"					,				attrs={"class": "gs_fl"}		).find_all("a"		)
 return anchors[2].get_text()


if __name__ == "__main__":
     a_  :				str						= {
         """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))







'''simple docstring'''

a_  :				Any						= """0.21.0"""

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
     from .utils import rich



