





import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict

@dataclass
class 		SCREAMING_SNAKE_CASE__				(       _UpperCAmelCase  ):
      A_						:				Union[str, Any]							=    ComputeEnvironment.AMAZON_SAGEMAKER
      A_						:				List[Any]							=    True
      A_						:				Tuple							=    'ml.p3.2xlarge'
      A_						:				Union[str, Any]							=    'accelerate_sagemaker_execution_role'
      A_						:				str							=    'hf-sm'
      A_						:				str							=    'us-east-1'
      A_						:				Tuple							=    1
      A_						:				int							=    'accelerate-sagemaker-1'
      A_						:				Union[str, Any]							=    '1.6'
      A_						:				Tuple							=    '4.4'
      A_						:				Optional[Any]							=    'train.py'
      A_						:				Optional[Any]							=    [
          '--model_name_or_path',
          'bert',
          '--do_train',
          'False',
          '--epochs',
          '3',
          '--learning_rate',
          '5e-5',
          '--max_steps',
          '50.5',
      ]
      A_						:				Dict							=    [
          '--model_name_or_path',
          'bert',
          '--do_train',
          '--do_test',
          'False',
          '--do_predict',
          '--epochs',
          '3',
          '--learning_rate',
          '5e-5',
          '--max_steps',
          '50.5',
      ]






class 		SCREAMING_SNAKE_CASE__				(       unittest.TestCase  ):


      def    a (self       :      Dict      ):





         """simple docstring"""



         __snake_case							       =   _convert_nargs_to_dict(MockLaunchConfig.success_training_script_args      )
         assert isinstance(converted_args['''model_name_or_path''']				,			a__      )
         assert isinstance(converted_args['''do_train''']				,			a__      )
         assert isinstance(converted_args['''epochs''']				,			a__      )
         assert isinstance(converted_args['''learning_rate''']				,			a__      )
         assert isinstance(converted_args['''max_steps''']				,			a__      )

         with pytest.raises(a__      ):
            _convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args      )





def 		lowercase_(  SCREAMING_SNAKE_CASE_ = 4000000	):


  '''simple docstring'''

  lowerCamelCase :					Any    =				[0, 1]
  lowerCamelCase :					Union[str, Any]    =				0
  while fib[i] <= n:
    fib.append(fib[i] + fib[i + 1]	)
    if fib[i + 2] > n:
      break
    i += 1
  lowerCamelCase :					Union[str, Any]    =				0
  for j in range(len(SCREAMING_SNAKE_CASE_	) - 1	):
    if fib[j] % 2 == 0:
      total += fib[j]

  return total


if __name__ == "__main__":
   print(f'''{solution() = }''')



