


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)

SCREAMING_SNAKE_CASE			: Optional[Any]				   =					logging.getLogger()



def 							UpperCamelCase_( )       ->		Optional[Any]:
    _lowercase			:				Tuple 						=						argparse.ArgumentParser()
    parser.add_argument('-f'					)
    _lowercase			:				List[str] 						=						parser.parse_args()
    return args.f






class _lowerCamelCase(		_a  ):
       def      UpperCamelCase	(   self)			->  None:




           """simple docstring"""

           _lowercase			:				Tuple 						=						logging.StreamHandler(sys.stdout)
           logger.addHandler(lowerCamelCase)
       def      UpperCamelCase	(   self, lowerCamelCase)			->  Dict:




           """simple docstring"""

           _lowercase			:				int 						=						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(lowerCamelCase, 'argv', lowerCamelCase):
                   _lowercase			:				Optional[Any] 						=						run_glue_deebert.main()
                   for value in result.values():
                       self.assertGreaterEqual(lowerCamelCase, 0.6_6_6)




       @slow
       @require_torch_non_multi_gpu
       def      UpperCamelCase	(   self)			->  Union[str, Any]:




           """simple docstring"""

           _lowercase			:				str 						=						'\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(lowerCamelCase)

           _lowercase			:				Optional[int] 						=						'\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(lowerCamelCase)

           _lowercase			:				Optional[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(lowerCamelCase)






from maths.prime_factors import prime_factors



def 							UpperCamelCase_( lowerCamelCase_					)       ->		int:
    if not isinstance(lowerCamelCase_				,					lowerCamelCase_					):
        _lowercase			:				str 						=						F'''Input value of [number={number}] must be an integer'''
        raise TypeError(lowerCamelCase_					)
    if number < 1:
        raise ValueError('Input must be a positive integer'					)
    return -1 if len(prime_factors(lowerCamelCase_					)					) % 2 else 1


if __name__ == "__main__":
 import doctest

 doctest.testmod()


