

"""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)

a					:List[str]    = logging.getLogger()




def  _lowercase					(    )       ->				int:
      SCREAMING_SNAKE_CASE__   :      List[str]      		=	argparse.ArgumentParser()
      parser.add_argument("""-f"""							)
      SCREAMING_SNAKE_CASE__   :      str      		=	parser.parse_args()
      return args.f



class      __a							(UpperCamelCase_):






     '''simple docstring'''

     def 					_a			(						self  )  ->      None:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	logging.StreamHandler(sys.stdout  )
           logger.addHandler(_a  )

     def 					_a			(						self	,    _a  )  ->      Tuple:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      List[str]      		=	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(_a	,    """argv"""	,    _a  ):
                       SCREAMING_SNAKE_CASE__   :      Dict      		=	run_glue_deebert.main()
                       for value in result.values():
                             self.assertGreaterEqual(_a	,    0.666  )





     @slow
     @require_torch_non_multi_gpu
     def 					_a			(						self  )  ->      Optional[Any]:


           """simple docstring"""


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

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

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







"""simple docstring"""


a					:List[str]    = [
    (1_000, "M"),
    (900, "CM"),
    (500, "D"),
    (400, "CD"),
    (100, "C"),
    (90, "XC"),
    (50, "L"),
    (40, "XL"),
    (10, "X"),
    (9, "IX"),
    (5, "V"),
    (4, "IV"),
    (1, "I"),
]




def  _lowercase					(    __lowerCAmelCase							)       ->				int:
      SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	{"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1000}
      SCREAMING_SNAKE_CASE__   :      List[Any]      		=	0
      SCREAMING_SNAKE_CASE__   :      List[str]      		=	0
      while place < len(__lowerCAmelCase							):
            if (place + 1 < len(__lowerCAmelCase							)) and (vals[roman[place]] < vals[roman[place + 1]]):
                  total += vals[roman[place + 1]] - vals[roman[place]]
                  place += 2
            else:
                  total += vals[roman[place]]
                  place += 1
      return total




def  _lowercase					(    __lowerCAmelCase							)       ->				str:
      SCREAMING_SNAKE_CASE__   :      Any      		=	[]
      for arabic, roman in ROMAN:
            ((SCREAMING_SNAKE_CASE__)		,		(SCREAMING_SNAKE_CASE__))   :      List[str]      		=	divmod(__lowerCAmelCase  ,					__lowerCAmelCase							)
            result.append(roman * factor							)
            if number == 0:
                  break
      return "".join(__lowerCAmelCase							)


if __name__ == "__main__":
  import doctest

  doctest.testmod()




