

'''simple docstring'''







import os
import sys

__lowerCamelCase						    =      os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


__lowerCamelCase						    =      [
    '''torch''',
    '''numpy''',
    '''tokenizers''',
    '''filelock''',
    '''requests''',
    '''tqdm''',
    '''regex''',
    '''sentencepiece''',
    '''sacremoses''',
    '''importlib_metadata''',
    '''huggingface_hub''',
]
@add_start_docstrings(AutoConfig.__doc__			)
def  UpperCAmelCase__      ( *UpperCAmelCase__,    **UpperCAmelCase__			)     ->     List[str]:
       return AutoConfig.from_pretrained(*UpperCAmelCase__,    **UpperCAmelCase__			)
@add_start_docstrings(AutoTokenizer.__doc__			)
def  UpperCAmelCase__      ( *UpperCAmelCase__,    **UpperCAmelCase__			)     ->     str:
       return AutoTokenizer.from_pretrained(*UpperCAmelCase__,    **UpperCAmelCase__			)
@add_start_docstrings(AutoModel.__doc__			)
def  UpperCAmelCase__      ( *UpperCAmelCase__,    **UpperCAmelCase__			)     ->     Tuple:
       return AutoModel.from_pretrained(*UpperCAmelCase__,    **UpperCAmelCase__			)
@add_start_docstrings(AutoModelForCausalLM.__doc__			)
def  UpperCAmelCase__      ( *UpperCAmelCase__,    **UpperCAmelCase__			)     ->     Dict:
       return AutoModelForCausalLM.from_pretrained(*UpperCAmelCase__,    **UpperCAmelCase__			)
@add_start_docstrings(AutoModelForMaskedLM.__doc__			)
def  UpperCAmelCase__      ( *UpperCAmelCase__,    **UpperCAmelCase__			)     ->     Any:
       return AutoModelForMaskedLM.from_pretrained(*UpperCAmelCase__,    **UpperCAmelCase__			)
@add_start_docstrings(AutoModelForSequenceClassification.__doc__			)
def  UpperCAmelCase__      ( *UpperCAmelCase__,    **UpperCAmelCase__			)     ->     int:
       return AutoModelForSequenceClassification.from_pretrained(*UpperCAmelCase__,    **UpperCAmelCase__			)







@add_start_docstrings(AutoModelForQuestionAnswering.__doc__			)
def  UpperCAmelCase__      ( *UpperCAmelCase__,    **UpperCAmelCase__			)     ->     Dict:
       return AutoModelForQuestionAnswering.from_pretrained(*UpperCAmelCase__,    **UpperCAmelCase__			)



'''simple docstring'''







import requests

__lowerCamelCase						    =      ''''''  # <-- Put your OpenWeatherMap appid here!
__lowerCamelCase						    =      '''https://api.openweathermap.org/data/2.5/'''
def  UpperCAmelCase__      ( UpperCAmelCase__ = "Chicago",    UpperCAmelCase__ = APPID			)     ->     dict:
       return requests.get(URL_BASE + """weather""",    params=locals()			).json()
def  UpperCAmelCase__      ( UpperCAmelCase__ = "Kolkata, India",    UpperCAmelCase__ = APPID			)     ->     dict:
       return requests.get(URL_BASE + """forecast""",    params=locals()			).json()
def  UpperCAmelCase__      ( UpperCAmelCase__ = 55.68,    UpperCAmelCase__ = 12.57,    UpperCAmelCase__ = APPID			)     ->     dict:
       return requests.get(URL_BASE + """onecall""",    params=locals()			).json()


if __name__ == "__main__":
      from pprint import pprint

      while True:
            __lowerCamelCase						    =      input('''Enter a location:''').strip()
            if location:
                  pprint(current_weather(location))
            else:
                  break
