

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     (  a_			):
  """simple docstring"""






  lowerCamelCase   :      Tuple										=ComputeEnvironment.AMAZON_SAGEMAKER
  lowerCamelCase   :      Optional[Any]										=True
  lowerCamelCase   :      List[str]										="ml.p3.2xlarge"
  lowerCamelCase   :      Union[str, Any]										="accelerate_sagemaker_execution_role"
  lowerCamelCase   :      Tuple										="hf-sm"
  lowerCamelCase   :      List[Any]										="us-east-1"
  lowerCamelCase   :      List[str]										=1
  lowerCamelCase   :      List[str]										="accelerate-sagemaker-1"
  lowerCamelCase   :      List[str]										="1.6"
  lowerCamelCase   :      str										="4.4"
  lowerCamelCase   :      List[Any]										="train.py"
  lowerCamelCase   :      List[Any]										=[
      "--model_name_or_path",
      "bert",
      "--do_train",
      "False",
      "--epochs",
      "3",
      "--learning_rate",
      "5e-5",
      "--max_steps",
      "50.5",
  ]
  lowerCamelCase   :      Tuple										=[
      "--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			):
  """simple docstring"""






  def 	SCREAMING_SNAKE_CASE   (      self			:   int   )							->     Optional[int]:






     """simple docstring"""







     __lowerCAmelCase  :      int    =						_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args   )
     assert isinstance(converted_args["""model_name_or_path"""]	,							lowerCAmelCase   )
     assert isinstance(converted_args["""do_train"""]	,							lowerCAmelCase   )
     assert isinstance(converted_args["""epochs"""]	,							lowerCAmelCase   )
     assert isinstance(converted_args["""learning_rate"""]	,							lowerCAmelCase   )
     assert isinstance(converted_args["""max_steps"""]	,							lowerCAmelCase   )

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





from __future__ import annotations





def      snake_case_				(__A					:						list[float] ,       __A					:						list[float]					)      ->     float:
   __lowerCAmelCase  :      Union[str, Any]    =						sorted(numsa + numsa					)
   __lowerCAmelCase   ,__lowerCAmelCase  :      Optional[int]    =						divmod(len(__A					) ,       2					)
   if mod == 1:
      return all_numbers[div]
   else:
      return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   __UpperCAmelCase								=			[float(x) for x in input("""Enter the elements of first array: """).split()]
   __UpperCAmelCase								=			[float(x) for x in input("""Enter the elements of second array: """).split()]
   print(F'The median of two arrays is: {median_of_two_arrays(array_a, array_a)}')


