





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				)









from __future__ import annotations

from collections import namedtuple





def 						__SCREAMING_SNAKE_CASE  (				UpperCamelCase__			,			UpperCamelCase__			,			UpperCamelCase__ )  ->				tuple:







			'''simple docstring'''

			UpperCAmelCase   		=				namedtuple('''result'''			,			'''name value''' )
			if (voltage, current, power).count(0 ) != 1:
						raise ValueError('''Only one argument must be 0''' )
			elif power < 0:
						raise ValueError(
						    '''Power cannot be negative in any electrical/electronics system''' )
			elif voltage == 0:
						return result('''voltage'''			,			power / current )
			elif current == 0:
						return result('''current'''			,			power / voltage )
			elif power == 0:
						return result('''power'''			,			float(round(abs(voltage * current )			,			2 ) ) )
			else:
						raise ValueError('''Exactly one argument must be 0''' )


if __name__ == "__main__":
				import doctest

				doctest.testmod()



