



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case						:List[str]      		=     {
    """configuration_upernet""": ["""UperNetConfig"""],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __snake_case						:List[str]      		=     [
     """UperNetForSemanticSegmentation""",
     """UperNetPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_upernet import UperNetConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel


else:
 import sys

 __snake_case						:int      		=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






'''simple docstring'''

import requests

__a: str          =   """https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""
def 			__UpperCamelCase       (   UpperCAmelCase     ):
 # fetching a list of articles in json format
 lowercase__				:    Optional[Any]  =					requests.get(_NEWS_API + bbc_news_api_key     ).json()
 # each article in the list is a dict
 for i, article in enumerate(bbc_news_page['''articles''']		,     1     ):
  print(F"""{i}.) {article['title']}"""     )


if __name__ == "__main__":
  fetch_bbc_news(bbc_news_api_key="""<Your BBC News API key goes here>""")

