


import os

import pytest
from attr import dataclass


UpperCAmelCase_   :				Union[str, Any]						      = 'us-east-1'  # defaults region
@dataclass
class 				SCREAMING_SNAKE_CASE__						:
      snake_case__       :  str
      snake_case__       :  str       =		'''arn:aws:iam::558105141721:role/sagemaker_execution_role'''
      snake_case__       :  List[Any]       =		{
          '''task_name''': '''mnli''',
          '''per_device_train_batch_size''': 16,
          '''per_device_eval_batch_size''': 16,
          '''do_train''': True,
          '''do_eval''': True,
          '''do_predict''': True,
          '''output_dir''': '''/opt/ml/model''',
          '''overwrite_output_dir''': True,
          '''max_steps''': 500,
          '''save_steps''': 5_500,
      }
      snake_case__       :  Tuple       =		{**hyperparameters, '''max_steps''': 1_000}
      @property
      def  SCREAMING_SNAKE_CASE							( self       : Optional[int]  )	->    str:
             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  SCREAMING_SNAKE_CASE							( self       : int  )	->    str:
             return F"""{self.framework}-transfromers-test"""
      @property
      def  SCREAMING_SNAKE_CASE							( self       : Dict  )	->    str:
             return F"""./tests/sagemaker/scripts/{self.framework}"""

      @property
      def  SCREAMING_SNAKE_CASE							( self       : Optional[Any]  )	->    str:
             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  SCREAMING_SNAKE_CASE_		(    __A				:    Optional[int]       )			->	int:

       """simple docstring"""

       a_      :	Union[str, Any]							=						SageMakerTestEnvironment(framework=request.cls.framework       )






def  SCREAMING_SNAKE_CASE_		(    __A				:    int						,					__A				:    int						,					__A				:    int       )			->	float:

       """simple docstring"""

       a_      :	Optional[int]							=						(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
       # formula for sum of series
       return total







def  SCREAMING_SNAKE_CASE_		(    )			->	Optional[Any]:

       """simple docstring"""

       print(sum_of_series(1						,					1						,					10       )       )


if __name__ == "__main__":
   import doctest

   doctest.testmod()


