


"""simple docstring"""



import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

__snake_case       =       logging.getLogger()







def     __lowerCAmelCase		(		)      ->		str:


    """simple docstring"""





    snake_case       : Union[str, Any]    =       argparse.ArgumentParser()
    parser.add_argument("-f"					)
    snake_case       : Optional[int]    =       parser.parse_args()
    return args.f







class _lowerCAmelCase							( snake_case_      ):







   def 					lowerCamelCase						(      self		)      ->						None:

       '''simple docstring'''




       snake_case       : int    =       logging.StreamHandler(sys.stdout		)
       logger.addHandler(UpperCamelCase__		)







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		)      ->						Optional[Any]:

       '''simple docstring'''




       snake_case       : List[Any]    =       get_gpu_count()

       if n_gpu > 1:
           pass
           # XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
           # script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
           # distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
           # cmd = [sys.executable] + distributed_args + args
           # execute_subprocess_async(cmd, env=self.get_env())
           # XXX: test the results - need to save them first into .json file
       else:
           args.insert(0		,      "run_glue_deebert.py"		)
           with patch.object(UpperCamelCase__		,      "argv"		,      UpperCamelCase__		):
               snake_case       : Optional[Any]    =       run_glue_deebert.main()
               for value in result.values():
                   self.assertGreaterEqual(UpperCamelCase__		,      0.666		)







   @slow
   @require_torch_non_multi_gpu
   def 					lowerCamelCase						(      self		)      ->						Tuple:

       '''simple docstring'''




       snake_case       : Union[str, Any]    =       "\n            --model_type roberta\n            --model_name_or_path roberta-base\n            --task_name MRPC\n            --do_train\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --max_seq_length 128\n            --per_gpu_eval_batch_size=1\n            --per_gpu_train_batch_size=8\n            --learning_rate 2e-4\n            --num_train_epochs 3\n            --overwrite_output_dir\n            --seed 42\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --save_steps 0\n            --overwrite_cache\n            --eval_after_first_stage\n            ".split()
       self.run_and_check(UpperCamelCase__		)

       snake_case       : Dict    =       "\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --eval_each_highway\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            ".split()
       self.run_and_check(UpperCamelCase__		)

       snake_case       : Union[str, Any]    =       "\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --early_exit_entropy 0.1\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            ".split()
       self.run_and_check(UpperCamelCase__		)









"""simple docstring"""



import string







def     __lowerCAmelCase		(		lowercase    :    str					)      ->		None:


    """simple docstring"""





    for key in range(len(string.ascii_uppercase					)					):
        snake_case       : Dict    =       ""
        for symbol in message:
            if symbol in string.ascii_uppercase:
                snake_case       : Dict    =       string.ascii_uppercase.find(lowercase					)
                snake_case       : Optional[int]    =       num - key
                if num < 0:
                    snake_case       : Optional[int]    =       num + len(string.ascii_uppercase					)
                snake_case       : Dict    =       translated + string.ascii_uppercase[num]
            else:
                snake_case       : Any    =       translated + symbol
        print(F'Decryption using Key #{key}: {translated}'					)







def     __lowerCAmelCase		(		)      ->		None:


    """simple docstring"""





    snake_case       : Dict    =       input("Encrypted message: "					)
    snake_case       : Any    =       message.upper()
    decrypt(lowercase					)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()





