





import os

import pytest
from attr import dataclass


lowercase      :       Any									=  """us-east-1"""  # defaults region





@dataclass
class  A__    :




   """simple docstring"""



   __A   :				str
   __A   :				str         =  '''arn:aws:iam::558105141721:role/sagemaker_execution_role'''
   __A   :				Optional[Any]         =  {
       '''task_name''': '''mnli''',
       '''per_device_train_batch_size''': 1_6,
       '''per_device_eval_batch_size''': 1_6,
       '''do_train''': True,
       '''do_eval''': True,
       '''do_predict''': True,
       '''output_dir''': '''/opt/ml/model''',
       '''overwrite_output_dir''': True,
       '''max_steps''': 5_0_0,
       '''save_steps''': 5_5_0_0,
   }
   __A   :				List[str]         =  {**hyperparameters, '''max_steps''': 1_0_0_0}

   @property
   def 							__lowercase		(					self)			->						str:







          '''simple docstring'''

          if self.framework == "pytorch":
                 return [
                     {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
                     {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
                     {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
                 ]
          else:
                 return [
                     {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
                     {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
                     {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
                 ]

   @property
   def 							__lowercase		(					self)			->						str:







          '''simple docstring'''

          return F'{self.framework}-transfromers-test'

   @property
   def 							__lowercase		(					self)			->						str:







          '''simple docstring'''

          return F'./tests/sagemaker/scripts/{self.framework}'

   @property
   def 							__lowercase		(					self)			->						str:







          '''simple docstring'''

          if self.framework == "pytorch":
                 return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
          else:
                 return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"



@pytest.fixture(scope='class'				)
def A_	(		A__				)  ->		Dict:
       a__						:	int =				SageMakerTestEnvironment(framework=request.cls.framework				)









def A_	(		A__				)  ->		int:
       stooge(A__		,      0		,      len(A__				) - 1				)
       return arr



def A_	(		A__		,      A__		,      A__				)  ->		List[Any]:
       if i >= h:
              return

       # If first element is smaller than the last then swap them
       if arr[i] > arr[h]:
              a__ ,							a__						:	List[str] =				arr[h], arr[i]

       # If there are more than 2 elements in the array
       if h - i + 1 > 2:
              a__						:	Dict =				(int)((h - i + 1) / 3				)

              # Recursively sort first 2/3 elements
              stooge(A__		,      A__		,      (h - t)				)

              # Recursively sort last 2/3 elements
              stooge(A__		,      i + t		,      (A__)				)

              # Recursively sort first 2/3 elements
              stooge(A__		,      A__		,      (h - t)				)


if __name__ == "__main__":
    lowercase      :       Dict									=  input("""Enter numbers separated by a comma:\n""").strip()
    lowercase      :       Dict									=  [int(item) for item in user_input.split(""",""")]
    print(stooge_sort(unsorted))


