

'''simple docstring'''







import json
import logging
import os
import sys
from time import time
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, require_torch_tpu


logging.basicConfig(level=logging.DEBUG)

__lowerCamelCase						    =      logging.getLogger()
def  UpperCAmelCase__      ( UpperCAmelCase__			)     ->     int:
       A_		   = {}
       A_		   = os.path.join(UpperCAmelCase__,    """all_results.json"""			)
       if os.path.exists(UpperCAmelCase__			):
              with open(UpperCAmelCase__,    """r"""			) as f:
                     A_		   = json.load(UpperCAmelCase__			)
       else:
              raise ValueError(F'''can\'t find {path}'''			)
       return results


__lowerCamelCase						    =      logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







@require_torch_tpu
class    A__ ( _snake_case     ):



    def    snake_case_     (   self    )  -> List[str]:





           '''simple docstring'''
           import xla_spawn

           A_		   = self.get_auto_remove_tmp_dir()
           A_		   = f'''
            ./examples/pytorch/text-classification/run_glue.py
            --num_cores=8
            ./examples/pytorch/text-classification/run_glue.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --do_train
            --do_eval
            --debug tpu_metrics_debug
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --max_steps=10
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            '''.split()

           with patch.object(UpperCamelCase__						,			"""argv"""						,			UpperCamelCase__    ):
                  A_		   = time()
                  xla_spawn.main()
                  A_		   = time()

                  A_		   = get_results(UpperCamelCase__    )
                  self.assertGreaterEqual(result["""eval_accuracy"""]						,			0.75    )

                  # Assert that the script takes less than 500 seconds to make sure it doesn't hang.
                  self.assertLess(end - start						,			500    )







    def    snake_case_     (   self    )  -> Optional[Any]:





           '''simple docstring'''
           import xla_spawn

           A_		   = """
            ./tests/test_trainer_tpu.py
            --num_cores=8
            ./tests/test_trainer_tpu.py
            """.split()
           with patch.object(UpperCamelCase__						,			"""argv"""						,			UpperCamelCase__    ):
                  xla_spawn.main()



'''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
